JP2018163453A - Impression quantity estimation method, impression quantity estimation device and building design method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To easily estimate an impression quantity of an indoor space even when a design is changed for each part that constitutes the indoor space.SOLUTION: An impression quantity estimation method that estimates an impression quantity for a room recognized form a specific view point using a computer device has the steps of: acquiring input information including illumination information and day light information of the room; creating a luminance image on the basis of the input information; dividing the luminance image into pieces of information for each part entering the specific view point of the room from each part of the room; and calculating a value indicating the impression quantity on the basis of the information for each part of the room and a weighting to the information for each part of the room.SELECTED DRAWING: Figure 6

Description

  The present invention relates to an impression amount estimation method, an impression amount estimation device, and a building design method.

When evaluating the environment of an indoor space, it is important to grasp the brightness and impression that people feel about the indoor space. The illumination standard of Japanese Industrial Standard is often used for lighting design of indoor space.
In recent years, the importance of luminance has increased in light environment evaluation, and a space evaluation method using luminance has been proposed.
A method to predict the "brightness" that people feel more accurately and use it in the design has been proposed, but due to the ease of handling of illuminance, spatial design is still often performed by illuminance, The place depends on the experience and sense of the designer.

  Regarding the technology for evaluating the brightness environment of the space, the statistics of the luminance distribution and distribution status within the circle with a forward visual field of 180 degrees are obtained from the input image data, and the indoor space of different brightness environments is evaluated by the observer in advance. A technique is known in which a feeling of brightness is predicted by a brightness feeling prediction formula derived from evaluation data, and evaluation is performed using the prediction result (see, for example, Patent Document 1).

JP 2004-354200 A

  However, since the brightness of the indoor space is calculated as an average value of the focused space, it is difficult to apply the design to the interior of the indoor space. In addition, when designing an indoor space based on the experience and sense of an interior advisor, the result of the design of the indoor space may differ depending on the interior advisor.

  The present invention has been made in view of the above-described problems, and an impression amount estimation method capable of easily estimating the impression amount of an indoor space even when the design is changed for each part constituting the indoor space, An object is to provide an impression amount estimation device and a building design method.

  (1) In order to solve the above-described problem, an embodiment of the present invention is an impression amount estimation method for estimating an impression amount for a room recognized from a specific viewpoint using a computer device, and the illumination information of the room A step of acquiring input information including the daylight information, a step of generating a luminance image based on the input information, and a portion of the room entering the specific viewpoint from each portion of the room An impression amount estimation method comprising: dividing the information into each information; and calculating a value indicating an impression amount based on information for each part of the room and information for each part of the room .

According to the impression amount estimation method according to the present embodiment, input information including room illumination information and daylight information is acquired, a luminance image is generated based on the acquired input information, and the generated luminance image is The information is divided into information for each part of the room that enters a specific viewpoint from each part of the room. Then, based on the information for each part of the room and the weighting for the information for each part of the room, a value indicating the impression amount is calculated.
In this way, since the luminance image generated based on the input information is divided into information for each part of the room that enters a specific viewpoint from each part of the room, the luminance in life for each component surface such as each part of the room Can be easily grasped, so that it can be applied to space design.
Then, a value indicating the impression amount can be calculated based on the information for each part of the room and the weighting for the information for each part of the room. That is, a subjective impression amount felt by a person can be estimated from a physical quantity such as luminance information. Compared to the case where the brightness of the indoor space is calculated as the average value of the focused space, it is possible to select materials, select colors, select windows, etc. for each component surface. The application is easy, and the impression amount of the indoor space can be easily estimated even when the design is changed for each configuration surface constituting the indoor space. Since the user can grasp the value indicating the digitized impression amount, the impression amount can be evaluated at a certain level regardless of the experience and sense of the interior advisor.

  (2) In one embodiment of the present invention, in the impression amount estimation method described above, in the dividing step, the luminance image is obtained from ceiling information that enters a specific viewpoint from the ceiling of the room, and a wall of the room. Dividing into the wall information entering the specific viewpoint, the floor information entering the specific viewpoint from the floor of the room, and the window information entering the specific viewpoint from the window of the room, and in the step of calculating, The impression amount is indicated based on the ceiling information and the weight for the ceiling information, the weight for the wall information and the wall information, the weight for the floor information and the floor information, and the weight for the window information and the window information. The value may be calculated.

By configuring in this way, the generated luminance image is obtained by using the ceiling information that enters the specific viewpoint from the ceiling of the room, the wall information that enters the specific viewpoint from the wall of the room, and the floor that enters the specific viewpoint from the floor of the room. It can be divided into information and window information entering a specific viewpoint from the window of the room. The value indicating the impression amount based on the weighting for the ceiling information and the ceiling information, the weighting for the wall information and the wall information, the weighting for the floor information and the floor information, and the weighting for the window information and the window information. Can be calculated.
In this way, the brightness image generated based on the input information enters ceiling information that enters a specific viewpoint from the ceiling of the room, wall information that enters a specific viewpoint from the wall of the room, and enters a specific viewpoint from the floor of the room. Since it is divided into floor information and window information that enters the specific viewpoint from the window of the room, it is possible to easily grasp the level of luminance in daily life for each component surface such as the ceiling, wall, floor, and window. Can be applied to space design.
The value indicating the impression amount based on the weighting for the ceiling information and the ceiling information, the weighting for the wall information and the wall information, the weighting for the floor information and the floor information, and the weighting for the window information and the window information. Can be calculated. That is, a subjective impression amount felt by a person can be estimated from a physical quantity such as luminance information. Compared to the case where the brightness of the indoor space is calculated as the average value of the focused space, it is possible to select materials, select colors, select windows, etc. for each component surface. The application is easy, and the impression amount of the indoor space can be easily estimated even when the design is changed for each configuration surface constituting the indoor space. Since the user can grasp the value indicating the digitized impression amount, the impression amount can be evaluated at a certain level regardless of the experience and sense of the interior advisor.

  (3) One embodiment of the present invention has a step of generating a brightness image from the luminance image generated in the step of generating the luminance image in the impression amount estimation method described above, and in the step of dividing, The brightness image may be divided into information for each part of the room entering the specific viewpoint from each part of the room.

With this configuration, the brightness image generated from the luminance image can be divided into information for each part of the room that enters the specific viewpoint from each part of the room.
In this way, the brightness image generated from the luminance image is divided into information for each part of the room that enters the specific viewpoint from each part of the room, so that design is performed for each component surface such as each part of the room be able to.

  (4) In one embodiment of the present invention, in the impression amount estimation method described above, in the dividing step, the brightness image is obtained by adding ceiling information that enters a specific viewpoint from the ceiling of the room, and a wall of the room. Dividing into the wall information entering the specific viewpoint from the floor information, the floor information entering the specific viewpoint from the floor of the room, and the window information entering the specific viewpoint from the window of the room, and the step of calculating, Based on the weight for the ceiling information and the ceiling information, the weight for the wall information and the wall information, the weight for the floor information and the floor information, and the weight for the window information and the window information, The indicated value may be calculated.

With this configuration, the brightness image generated from the luminance image is converted into ceiling information that enters a specific viewpoint from the ceiling of the room, wall information that enters a specific viewpoint from the wall of the room, and specific information from the floor of the room. It can be divided into floor information entering the viewpoint and window information entering a specific viewpoint from the room window.
In this way, the brightness image generated from the luminance image has ceiling information that enters a specific viewpoint from the ceiling of the room, wall information that enters a specific viewpoint from the wall of the room, and a floor that enters a specific viewpoint from the floor of the room. Since it is divided into information and window information that enters the specific viewpoint from the window of the room, it is possible to design for each component surface such as a ceiling, a wall, a floor, and a window.

  (5) In one embodiment of the present invention, in the impression amount estimation method described above, in the calculating step, the geometric average of the ceiling information, the geometric average of the wall information, the geometric average of the floor information, and the window information The geometric average of the ceiling information, the geometric average of the wall information, the geometric average of the floor information, and the geometric average of the window information may be further calculated.

  With this configuration, the geometric average of ceiling information, the geometric average of wall information, the geometric average of floor information, and the geometric average of window information are calculated, and the geometric average of ceiling information, the geometric average of wall information, and floor information are calculated. Further, based on the geometric average of the window information and the geometric average of the window information, the value indicating the impression amount is calculated, and the impression amount for the room can be estimated based on the value indicating the impression amount obtained by the calculation. That is, a subjective impression amount felt by a person can be estimated from a physical quantity such as luminance information. Compared to the case where the brightness of the indoor space is calculated as the average value of the focused space, it is possible to select materials, colors, windows, etc. The application is easy, and the impression amount of the indoor space can be easily estimated even when the design is changed for each configuration surface constituting the indoor space.

  (6) One embodiment of the present invention has a step of generating a glare image from the luminance image generated in the step of generating the luminance image in the impression amount estimation method described above. In the step of dividing, The glare image may be divided into information for each part of the room entering the specific viewpoint from each part of the room.

With this configuration, the glare image generated from the luminance image can be divided into information for each part of the room that enters the specific viewpoint from each part of the room.
In this way, since the glare image generated from the luminance image is divided into information for each part of the room that enters the specific viewpoint from each part of the room, design is performed for each component surface such as each part of the room Can do.

  (7) In one embodiment of the present invention, in the impression amount estimation method described above, in the dividing step, the glare image is obtained from ceiling information entering the specific viewpoint from the ceiling of the room, and a wall of the room. The information may be divided into wall information entering the specific viewpoint, floor information entering the specific viewpoint from the floor of the room, and window information entering the specific viewpoint from the window of the room.

By configuring in this way, the glare image generated from the luminance image is converted into the ceiling information that enters the specific viewpoint from the ceiling of the room, the wall information that enters the specific viewpoint from the wall of the room, and the specific viewpoint from the floor of the room. It can be divided into floor information entering and window information entering a specific viewpoint from the window of the room.
In this way, the glare image generated from the luminance image has ceiling information that enters a specific viewpoint from the ceiling of the room, wall information that enters a specific viewpoint from the wall of the room, and floor information that enters a specific viewpoint from the floor of the room And window information entering the specific viewpoint from the window of the room, the design can be performed for each component surface such as a ceiling, a wall, a floor, and a window.

(8) In one embodiment of the present invention, in the impression amount estimation method described above, in the step of calculating, the maximum value of the ceiling information, the maximum value of the wall information, the maximum value of the floor information, and the window information A maximum value of the ceiling information, a maximum value of the wall information, a maximum value of the floor information, and a maximum value of the window information are further calculated. May be.
By configuring in this way, the maximum value of ceiling information, the maximum value of wall information, the maximum value of floor information, and the maximum value of window information are calculated, the maximum value of ceiling information, the maximum value of wall information, the floor information Further, based on the maximum value and the maximum value of the window information, a value indicating the impression amount can be calculated. That is, a subjective impression amount felt by a person can be estimated from a physical quantity such as luminance information. Discomfort due to glare in the indoor space can be evaluated for each component surface, so it is easy to determine if glare is a problem on the side where the line of sight is easily directed, so it can be easily applied to space design and Even when the design is changed for each component surface constituting the space, the impression amount of the indoor space can be easily estimated.

(9) An embodiment of the present invention is an impression amount estimation device that estimates an impression amount for a room recognized from a specific viewpoint, and obtains input information including room illumination information and daylight information A generation unit that generates a luminance image based on the input information, a division unit that divides the luminance image into information for each part of the room that enters the specific viewpoint from each part of the room, An impression amount estimation apparatus comprising: a calculation unit that calculates a value indicating an impression amount based on information for each part of a room and weighting for information for each part of the room.
The impression amount estimation apparatus according to an embodiment of the present invention is substantially the same invention except for the impression amount estimation method and the category, and has the same operations and effects.

(10) One embodiment of the present invention is a building design method using the impression amount estimation method according to any one of (1) to (8) above.
The building design method according to an embodiment of the present invention is substantially the same invention except for the impression amount estimation method and the category, and has the same operations and effects.

According to the present invention, the luminance image generated based on the input information is divided into information for each part of the room that enters a specific viewpoint from each part of the room. Since it is possible to easily grasp the brightness level in the space, it can be applied to space design.
Further, according to the present invention, based on the information for each part of the room and the weighting for the information for each part of the room, the value indicating the impression amount is calculated, and the impression amount obtained by the calculation is indicated. Based on the value, the impression amount for the room can be estimated. That is, a subjective impression amount felt by a person can be estimated from a physical quantity such as luminance information. Compared to the case where the brightness of the indoor space is calculated as the average value of the focused space, it is possible to select materials, select colors, select windows, etc. for each component surface. The application is easy, and the impression amount of the indoor space can be easily estimated even when the design is changed for each configuration surface constituting the indoor space. Since the user can grasp the value indicating the digitized impression amount, the impression amount can be evaluated at a certain level regardless of the experience and sense of the interior advisor.

It is a figure which shows an example of a structure of indoor space. It is a figure which shows an example of the hardware constitutions of the impression amount estimation apparatus 100 which concerns on embodiment. It is a functional block diagram of the impression amount estimation apparatus according to the embodiment. It is a figure which shows an example of the input screen of indoor space information. It is a figure which shows the example of a display of a luminance image. It is a flowchart which shows an example of operation | movement of the impression amount estimation apparatus which concerns on embodiment. It is a figure which shows the outline | summary of the space which performs simulation. It is a figure which shows the other example of indoor space. It is a figure which shows the other example of a structure of the indoor space of a building. It is a functional block diagram of the impression amount estimation apparatus which concerns on a modification. It is a flowchart which shows an example of operation | movement of the impression amount estimation apparatus which concerns on a modification. It is a figure which shows an example of a structure of indoor space.

Next, modes for carrying out the present invention will be described with reference to the drawings. Embodiment described below is only an example and embodiment to which this invention is applied is not restricted to the following embodiment.
Note that components having the same function are denoted by the same reference symbols throughout the drawings for describing the embodiments, and the repetitive description will be omitted.

(Impression amount estimation device)
The impression amount estimation device 100 according to the embodiment of the present invention is a computer device that evaluates the impression amount of the indoor space of a building. Specifically, the impression amount estimation apparatus 100 acquires input information including room information (hereinafter referred to as “indoor space information”) representing an indoor space indicating the shape of the room and the interior physical properties, and the acquired indoor space information is included in the acquired indoor space information. Based on this, a luminance image is generated. The impression amount estimation apparatus 100 divides the generated luminance image into each part of the room, and calculates information for each part of the room that enters a specific viewpoint from each part. Here, the part of the room means a part occupying a certain position in the room. Then, the impression amount estimation apparatus 100 calculates a value indicating the impression amount of the room based on each piece of information for each part and a weight for each piece of information for each part. The impression amount estimation apparatus 100 outputs an estimation result of the impression amount for the room based on a value indicating the obtained impression amount by calculation.

  Hereinafter, as an example, the description will be continued with respect to the case where a room structural surface such as a ceiling, wall, floor, or window is applied to each part of the room. In this case, the impression amount estimation apparatus 100 divides the generated luminance image into component surfaces such as a ceiling, a wall, a floor, and a window, and calculates information that enters a specific viewpoint from each component surface. Here, the specific viewpoint means a representative viewpoint of an assumed resident. Specifically, the resident's posture may be standing, sitting, floor, etc., and the specific viewpoint may be viewpoints at various positions in the height direction and width direction of the room. For example, the impression amount estimation apparatus 100 sets the viewpoint position according to the purpose of the room. Specifically, in the case of a basic space such as a kitchen, the impression amount estimation apparatus 100 sets the viewpoint position to a height of about 1500 mm (a female eye height) in front of the sink, In this case, the viewpoint position is set to 900 mm (floor seat) or 1200 mm (sofa seat) from the end of the wall. Moreover, when evaluating as a basic space, the impression amount estimation apparatus 100 sets a height of about 1200 mm to 1500 mm as a representative in the center of the room.

  Hereinafter, information that enters a specific viewpoint from the ceiling of the room is referred to as “ceiling information”, information that enters a specific viewpoint from the wall of the room is referred to as “wall information”, and information that enters a specific viewpoint from the floor of the room is referred to as “ It is called “floor information”, and information that enters a specific viewpoint from the window is called “window information”. Then, the impression amount estimation device 100 indicates the impression amount of the room based on each of the ceiling information, the wall information, the floor information, and the window information and the weighting for each of the ceiling information, the wall information, the floor information, and the window information. Calculate the value. The impression amount estimation apparatus 100 outputs an estimation result of the impression amount for the room based on a value indicating the obtained impression amount by calculation. The impression amount includes open feeling, comfort, likes and dislikes, dazzlingness, calmness, brightness, cheerfulness, peacefulness, liveliness, warmth, and the like.

(Composition of indoor space)
FIG. 1 is a diagram illustrating an example of a configuration of an indoor space of a building. An example of the shape of the indoor space is a quadrangular prism, and FIG. In FIG. 1, 20 indicates a viewpoint. Here, as an example, a description will be given of an indoor space that is recognized when viewing the direction from the front side of the paper to the back side of the paper. Note that the azimuth on the back side of the page when viewed from the front side of the page is north.
The indoor space includes a ceiling 1, a left side wall 2, a right side wall 3, a front wall 4, a floor 5, a window 11, and an illumination 13. The left side wall 2 is a wall that can be seen on the left side when viewed from the viewpoint 20 on the near side of the paper surface toward the back side of the paper surface. Further, the right side wall 3 is a wall that can be seen on the right side when viewed from the viewpoint 20 on the near side of the paper surface toward the back side of the paper surface. The front wall 4 is a wall that can be seen in the front when viewed from the viewpoint 20 on the near side of the paper surface toward the back side of the paper surface. The window 11 is a window attached to the right side wall 3.
Input information including the indoor space identification information for identifying the indoor space shown in FIG. 1 and the indoor space information is input to the impression amount estimating apparatus 100. Hereinafter, the description of the impression amount estimation device 100 will be continued.

(Configuration of impression amount estimation device)
FIG. 2 is a diagram illustrating an example of a hardware configuration of the impression amount estimation apparatus 100 according to the embodiment. The impression amount estimation device 100 includes a CPU (Central Processing Unit) 102, a ROM (Read Only Memory) 104, a RAM (Random Access Memory) 106, an input / output device 108, a communication module 110, an auxiliary storage device 112, and a bus 120. ing.

The CPU 102 reads a program or the like for controlling the operation of the impression amount estimation apparatus 100 from the ROM 104 or the auxiliary storage device 112, develops it on the RAM 106, and executes it.
The input / output device 108 displays an input screen for indoor space information, an evaluation result of the impression amount of the room, and the like. The input / output device 108 accepts user operations. The input / output device 108 includes a touch panel, a pointing device, a touch pad, a display, and the like.
The communication module 110 includes an NFC module, a wireless LAN module, and the like. Further, the communication module 110 may be configured by USB (Universal Serial Bus). The communication module 110 communicates with an external device by NFC, wireless LAN, or wired.
The auxiliary storage device 112 includes a flash memory, an HDD (Hard Disc Drive), an SSD (Solid State Drive), an SD (Secure Digital) card, and the like. The auxiliary storage device 112 stores a program executed by the CPU 102.

(Functional structure of impression amount estimation device)
FIG. 3 is a functional block diagram of the impression amount estimation apparatus according to the embodiment.
The impression amount estimation apparatus 100 includes an acquisition unit 152, an image generation unit 154, a division unit 156, a calculation unit 158, and an impression amount estimation unit 160 by causing the CPU 102 to execute a program developed from the auxiliary storage device 112 onto the RAM 106. It functions as a storage unit 162 and an output unit 164.

(Each functional configuration of impression amount estimation device)
Each functional configuration of the impression amount estimation apparatus 100 will be described in detail with reference to FIGS. 2 and 3. In the following, in describing each function of the impression amount estimation apparatus 100, a relationship with main hardware for realizing each functional block of the impression amount estimation apparatus 100 illustrated in FIG. 3 will also be described.
The acquisition unit 152 is realized by a command from the CPU 102 and the input / output device 108. The acquisition unit 152 acquires input information input by the user from the input / output device 108. The input information includes indoor space identification information and indoor space information. The indoor space identification information is information for uniquely identifying the indoor space when there are a plurality of indoor spaces, and is represented by characters, symbols, and the like. The indoor space information includes illumination information such as output information of light sources such as illumination installed in the room and information related to light distribution. Further, the indoor space information includes daylight information that is information indicating light inserted from a window installed in the room. The daylight information is obtained based on the area where the room is installed, the date and time, the direction, and the like.
When the impression amount estimation device 100 is activated, a screen for inputting the indoor space identification information is displayed on the input / output device 108. When the user inputs the indoor space identification information of the indoor space for estimating the impression amount on the screen for inputting the indoor space identification information, the input screen for the indoor space information is displayed.

FIG. 4 is a diagram illustrating an example of an input screen for indoor space information. The input screen 170 includes information indicating the room size such as the width 202, the depth 204, and the ceiling height 206 as the indoor space information. Here, the width 202 is a horizontal length between the left side wall 2 and the right side wall 3 included in the constituent surface of the indoor space. The depth 204 is the horizontal length between the viewpoint 20 and the front wall 4. The ceiling height 206 is the length of a perpendicular line extending from the ceiling 1 to the floor 5.
The indoor space information includes window information such as a window type 208, a window arrangement 210, and the number 212 of windows. A window type 208 indicates the type of window such as a sweep window, a waist high window, a high window, a ground window, and a full height vertically long window. The window arrangement 210 indicates an orientation in which windows such as east, west, north, and south are arranged. The number 212 of windows indicates the number of windows included in the indoor space. Furthermore, the indoor space information includes a window glass type 214 and presence / absence of window covering 216. The window glass type 214 indicates the type of window glass such as transparent glass and haze glass. Window covers indicate lace curtains.

The indoor space information includes material information indicating materials such as a wall color 218, a floor color 220, and a ceiling color 222. The wall color 218 indicates the color of the left side wall 2, the color of the right side wall 3, and the color of the front wall 4.
In addition to the information shown in FIG. 4, the indoor space information includes lighting information such as the type, output, position, number, and light distribution pattern of lighting fixtures. The type of lighting fixture indicates the type of lighting 13 such as a downlight or a spotlight. The output indicates the total luminous flux output from the illumination 13. The position indicates a position where the illumination 13 is attached. The number indicates the number of lights 13 included in the indoor space. The light distribution pattern indicates the spread of light from the illumination 13 such as general diffuse light distribution, direct light distribution, semi-direct light distribution, semi-indirect light distribution, and indirect light distribution.
Further, the indoor space information includes room installation information such as the area where the room is installed and the direction of the room.

The input information may include information other than the indoor space identification information and the indoor space information. For example, the input information may include date / time information for estimating the impression amount.
When the acquiring unit 152 acquires the indoor space identification information, the indoor space information, and the date / time information, the acquiring unit 152 outputs the acquired indoor space identification information, the indoor space information, and the date / time information to the image generating unit 154.
Further, the room space information input screen includes an evaluation value display button 224. The evaluation value display button 224 is a button that is pressed when the impression amount estimation result is displayed on the input / output device 108.

  The image generation unit 154 is realized by a command from the CPU 102. When the image generation unit 154 acquires the indoor space identification information, the indoor space information, and the date / time information from the acquisition unit 152, the image generation unit 154 uses the acquired indoor space information and the date / time information to determine the room at the date / time included in the date / time information. A luminance image LI in which an image indicating luminance is displayed on the ceiling 1, the left side wall 2, the right side wall 3, the front wall 4, the floor 5, and the window 11 is generated. Luminance is a unit solid angle and a luminous intensity per unit area, and luminance has three-dimensional information. Specifically, the image generation unit 154 generates the luminance image LI by using a radiosity method, a ray tracing method, or the like. By using the radiosity method, the final rendering result is more realistic because it simulates the behavior of light close to the real world. By using the ray tracing method to draw the image at that point by tracing back the ray that reaches a certain point, for example, if it is a ray, the reflectance of the surface of the object, transparency, refractive index An image that closely reflects the above is obtained. For this reason, by using the ray tracing method, the path of the light beam is calculated pixel by pixel, so that it is possible to draw with high image quality. The image generation unit 154 outputs the image information of the generated luminance image LI to the division unit 156.

  The dividing unit 156 is realized by an instruction from the CPU 102. The dividing unit 156 acquires the image information of the luminance image LI from the image generating unit 154. The dividing unit 156 performs image processing on the acquired luminance image LI, thereby performing a ceiling 1 part, a left side wall 2 part, a right side wall 3 part, a front wall 4 part, a floor 5 part, and a window 11 part. Divide into That is, the dividing unit 156 acquires the ceiling luminance image 1a that enters the specific viewpoint from the ceiling of the room by dividing the luminance image LI into the ceiling 1 portion. In addition, the dividing unit 156 acquires the left side wall luminance image 2a entering the specific viewpoint from the left side wall 2 of the room by dividing the luminance image LI into the left side wall 2 portion. Further, the dividing unit 156 acquires the right side wall luminance image 3a that enters the specific viewpoint from the right side wall 3 of the room by dividing the luminance image LI into the right side wall 3 portion. Further, the dividing unit 156 acquires the front wall luminance image 4a entering the specific viewpoint from the front wall 4 of the room by dividing the luminance image LI into the front wall 4 portions. In addition, the dividing unit 156 acquires the floor luminance image 5 a that enters a specific viewpoint from the floor 5 of the room by dividing the luminance image LI into portions of the floor 5. In addition, the dividing unit 156 acquires the window luminance image 11 a entering the specific viewpoint from the window 11 in the room by dividing the luminance image LI into the window 11 portions.

FIG. 5 is a diagram illustrating a display example of the luminance image LI. FIG. 5 shows a ceiling luminance image 1a, a left side wall luminance image 2a, a right side wall luminance image 3a, a front wall luminance image 4a, a floor luminance image, 5a, and a window luminance image 11a included in the luminance image LI. . In FIG. 5, the details of the image showing the luminance itself are omitted. Further, FIG. 5 shows a pixel 300 that is a minimum unit of color information displayed on the screen of the input / output device 108 such as a display device.
The dividing unit 156 includes image information of the ceiling luminance image 1a, image information of the left side wall luminance image 2a, image information of the right side wall luminance image 3a, image information of the front wall luminance image 4a, image information of the floor luminance image 5a, and window luminance. The image 11a is output to the calculation unit 158.
The arithmetic unit 158 is realized by an instruction from the CPU 102. The calculation unit 158 outputs the image information of the ceiling luminance image 1a, the image information of the left side wall luminance image 2a, the image information of the right side wall luminance image 3a, the image information of the front wall luminance image 4a, and the floor luminance image output from the dividing unit 156. The image information 5a and the window luminance image 11a are acquired. The calculation unit 158 calculates the number of pixels included in each of the ceiling luminance image 1a, the left side wall luminance image 2a, the right side wall luminance image 3a, the front wall luminance image 4a, the floor luminance image 5a, and the window luminance image 11a. The calculation unit 158 calculates the calculation result of the number of pixels included in each of the ceiling luminance image 1a, the left side wall luminance image 2a, the right side wall luminance image 3a, the front wall luminance image 4a, the floor luminance image 5a, and the window luminance image 11a. Associate with indoor space identification information.

Further, the calculation unit 158 includes each of the ceiling luminance image 1a, left side wall luminance image 2a, right side wall luminance image 3a, front wall luminance image 4a, floor luminance image 5a, and window luminance image 11a in each luminance image. The luminance (logarithmic value) for each pixel is read, and the geometric average of the read luminance is calculated. Here, the geometric mean is obtained by taking the root of the product of the read luminances (the nth root if the number is n). The calculation unit 158 calculates the geometric average of the luminance obtained from the ceiling luminance image 1a, the calculation result of the geometric average of the luminance obtained from the left side wall luminance image 2a, and the luminance obtained from the right side wall luminance image 3a. Obtained from the front luminance image 4a, the geometric average calculation result obtained from the front wall luminance image 4a, the geometric average calculation result obtained from the floor luminance image 5a, and the window luminance image 11a. The calculation result of the geometric average of the brightness is associated with the indoor space identification information.
Hereinafter, the calculation result of the geometric average of the luminance obtained from the ceiling luminance image 1a is obtained from the ceiling luminance information, and the calculation result of the geometric average of the luminance obtained from the left side wall luminance image 2a is obtained from the left side wall luminance information and the right side wall luminance image 3a. The calculation result of the obtained geometric average of the luminance is the right side wall luminance information, the calculation result of the luminance geometric average obtained from the front wall luminance image 4a is the front wall luminance information, and the geometric average of the luminance obtained from the floor luminance image 5a. The calculation result is referred to as floor luminance information, and the calculation result of the geometric mean of luminance obtained from the window luminance image 11a is referred to as window luminance information.

The calculation unit 158 adds the calculation results of the number of pixels included in each of the ceiling luminance image 1a, the left side wall luminance image 2a, the right side wall luminance image 3a, the front wall luminance image 4a, the floor luminance image 5a, and the window luminance image 11a. To do. Hereinafter, a result obtained by summing up the calculation results of the number of pixels included in each of the ceiling luminance image 1a, the left side wall luminance image 2a, the right side wall luminance image 3a, the front wall luminance image 4a, the floor luminance image 5a, and the window luminance image 11a. , The number of pixels in the entire image
The calculation unit 158 obtains a pixel ratio of the ceiling luminance image 1a with respect to the entire image by dividing the number of pixels included in the ceiling luminance image 1a by the number of pixels of the entire image. Hereinafter, the pixel ratio with respect to all the images of the ceiling luminance image 1a is referred to as a ceiling pixel ratio.
In addition, the calculation unit 158 calculates the pixel ratio of the left side wall luminance image 2a with respect to the entire image by dividing the number of pixels included in the left side wall luminance image 2a by the number of pixels of the entire image. Hereinafter, the pixel ratio of the left side wall luminance image 2a with respect to the entire image is referred to as a left side wall pixel ratio.

In addition, the calculation unit 158 obtains a pixel ratio of the right side wall luminance image 3a with respect to the entire image by dividing the number of pixels included in the right side wall luminance image 3a by the number of pixels of the entire image. Hereinafter, the pixel ratio of the right side wall luminance image 3a with respect to the entire image is referred to as a right side wall pixel ratio.
In addition, the calculation unit 158 obtains the pixel ratio of the front wall luminance image 4a with respect to the entire image by dividing the number of pixels included in the front wall luminance image 4a by the number of pixels of the entire image. Hereinafter, the pixel ratio of the front wall luminance image 4a to the entire image is referred to as a front wall pixel ratio.
In addition, the calculation unit 158 obtains a pixel ratio of the floor luminance image 5a with respect to the entire image by dividing the number of pixels included in the floor luminance image 5a by the number of pixels of the entire image. Hereinafter, the pixel ratio of the floor luminance image 5a to the entire image is referred to as a floor pixel ratio.
In addition, the calculation unit 158 obtains a pixel ratio of the window luminance image 11a to the entire image by dividing the number of pixels included in the window luminance image 11a by the number of pixels of the entire image. Hereinafter, the pixel ratio of the window luminance image 11a to the entire image is referred to as a window pixel ratio.

  The calculation unit 158 includes the obtained ceiling pixel ratio, left side wall pixel ratio, right side wall pixel ratio, front wall pixel ratio, floor pixel ratio, and window pixel ratio, ceiling luminance information, left side wall luminance information, right side wall luminance information, By substituting the front wall luminance information, floor luminance information, and window luminance information into the impression amount estimation formula stored in the storage unit 162, a value indicating the impression amount is calculated. Specifically, the estimation formula for the impression amount is expressed by Expression (1). The derivation of the impression amount estimation formula will be described later.

  Estimated value of impression amount = A + B (ceiling luminance information × ceiling pixel ratio) + C (left side wall luminance information × left side wall pixel ratio) + D (right side wall luminance information × right side wall pixel ratio) + E (front wall luminance information × front wall pixel) Ratio) + F (floor luminance information × floor pixel ratio) + G (window luminance information × window pixel ratio) (1)

In Expression (1), A, B, C, D, E, F, and G are real numbers, and are set in advance by the administrator of the impression amount estimation apparatus 100. A is a constant, B is a weight for ceiling luminance information, C is a weight for left side wall luminance information, D is a weight for right side wall luminance information, E is a weight for front wall luminance information, F Is a weight for the floor luminance information, and G is a weight for the window luminance information.
Note that A, B, C, D, E, F, and G are estimated impression amounts that are open, comfortable, like, dislike, dazzling, calm, brightness, cheerful, peaceful, lively, or warm. It takes different values depending on whether or not.

The calculation unit 158 outputs a value indicating the impression amount to the impression amount estimation unit 160.
The impression amount estimation unit 160 is realized by a command from the CPU 102. The impression amount estimation unit 160 estimates the impression amount for the room based on the value indicating the impression amount output by the calculation unit 158. Specifically, the impression amount estimation unit 160 estimates that the impression is good when the value indicating the impression amount is equal to or larger than the impression amount threshold, and impresses when the value indicating the impression amount is less than the impression amount threshold. Is estimated to be bad. The impression amount estimation unit 160 outputs information indicating the impression amount estimation result to the output unit 164.
The storage unit 162 is realized by the auxiliary storage device 112. The storage unit 162 stores an impression amount estimation formula.
The output unit 164 is realized by the input / output device 108. The output unit 164 outputs the impression amount estimation result acquired from the impression amount estimation unit 160. Specifically, the output unit 164 outputs the impression amount estimation result to the input / output device 108 such as a display as an evaluation value of openness, an evaluation value of comfort, or an evaluation value of likes and dislikes, or a communication module. Or output to another device via 110.

(Operation of impression amount estimation device)
FIG. 6 is a flowchart illustrating an example of the operation of the impression amount estimation apparatus according to the embodiment.
(Step S <b> 102) The acquisition unit 152 acquires input information input by the user operating the input / output device 108. The acquisition unit 152 outputs the acquired input information to the image generation unit 154. As described above, the input information includes indoor space identification information, indoor space information, and date / time information.
(Step S <b> 104) When the image generation unit 154 acquires the input information output by the acquisition unit 152, the image generation unit 154 generates a luminance image LI using the indoor space information and the date / time information included in the acquired input information. This luminance image LI is an image showing luminance on the ceiling 1, left side wall 2, right side wall 3, front wall 4, floor 5 and window 11 of the room.

(Step S106) The dividing unit 156 divides the luminance image LI into a ceiling luminance image 1a, a left side wall luminance image 2a, a right side wall luminance image 3a, a front wall luminance image 4a, a floor luminance image 5a, and a window luminance image 11a. .
(Step S108) The computing unit 158 calculates the number of pixels included in each of the ceiling luminance image 1a, the left side wall luminance image 2a, the right side wall luminance image 3a, the front wall luminance image 4a, the floor luminance image 5a, and the window luminance image 11a. Calculate. The calculation unit 158 calculates the calculation result of the number of pixels included in each of the ceiling luminance image 1a, the left side wall luminance image 2a, the right side wall luminance image 3a, the front wall luminance image 4a, the floor luminance image 5a, and the window luminance image 11a. Associate with indoor space identification information.

  In addition, the calculation unit 158 calculates the luminance for each pixel included in each of the ceiling luminance image 1a, the left side wall luminance image 2a, the right side wall luminance image 3a, the front wall luminance image 4a, the floor luminance image 5a, and the window luminance image 11a. By reading and calculating the geometric average of the read luminances, ceiling luminance information, left side wall luminance information, right side wall luminance information, front wall luminance information, floor luminance information, and window luminance information are obtained.

The calculation unit 158 calculates the number of pixels included in each of the ceiling luminance image 1a, the left side wall luminance image 2a, the right side wall luminance image 3a, the front wall luminance image 4a, the floor luminance image 5a, and the window luminance image 11a. The ceiling pixel ratio, left side wall pixel ratio, right side wall pixel ratio, front wall pixel ratio, floor pixel ratio, and window pixel ratio are calculated. The calculation unit 158 substitutes each pixel ratio, ceiling luminance information, left side wall luminance information, right side wall luminance information, front wall luminance information, floor luminance information, and window luminance information into the impression amount estimation formula, thereby obtaining an impression. A value indicating the quantity is calculated.
(Step S110) The impression amount estimation unit 160 estimates the impression amount for the room based on the value indicating the impression amount.

(Derivation example of impression amount estimation formula)
An example of deriving an impression amount estimation formula will be described.
In order to derive an estimation formula for the impression amount, windows are arranged in various patterns in a space assuming LDK to simulate the light environment, and an estimated value of the impression amount is calculated. As an example of the impression amount estimation formula, a prediction formula obtained from the analysis result of the subject experiment is used.

(Simulation conditions)
FIG. 7 is a diagram showing an outline of a space in which simulation is performed.
The location of the building is a residential area in an urban area, assuming a two-story house with a long north and south, surrounded by a two-story neighbor. The height of the building and the neighbor was both Xmm. The distance to the neighbor was assumed to be about Ymm in the east and west, Zmm in the south, and Wmm in the north, assuming a garden in the south of the building and the north neighbor. The plane scale of the building is the same as that of the simulation space for convenience. Assuming a general LDK space, the simulation space is the first floor portion of the building, and the scale is Jmm in the east-west direction, Kmm in the north-south direction, and the ceiling height Lmm. The height of the first floor was Mmm from the ground.

(Window pattern)
Windows were arranged in various patterns in the simulation space. The window types were sweep window, waist high window (3 types of height), high window, ground window (2 types of height), and full-height vertical window, and the pattern was developed by changing the position and width. The number of patterns is 227 patterns for the total east and west layout, and the “impression amount” is calculated for 118 patterns for the east layout.
(Window glass type, window hanger)
The south surface sweeping window was made of transparent glass, and the window was equipped with a lace curtain. For the windows other than the south side, the glass type was made of hazy glass, assuming that the line of sight from the neighbors was relaxed, and there was no windowing except for the sweep window. In addition to the haze glass, lace curtains were installed at the sweep windows outside the south side.

(Gaze direction, viewpoint)
The line-of-sight directions were four directions, east, west, south, and north as shown in FIG. The viewpoint position was the center of the plane in the north-south direction, and the position was lowered from the center of the plane to the back wall in the east-west direction. The visual height was uniformly 1500 mm from the floor.
(Times of Day)
The simulation time was every 30 minutes from 7:00 to 16:00 for two days, the summer solstice (June 22) and the winter solstice (December 22).
As described above, the number of simulation calculations performed is 4 directions × 2 days × 19 time = 152 cases per window arrangement pattern, and the total number of windows in the east surface arrangement 118 is 17936.

(Create 3D model)
The 3D model mainly specializes in reproducing the surface of the simulation space, omitting parts that do not affect the light environment.

(Luminance image analysis)
The data obtained from the ray-tracing calculation results were analyzed and converted to data for calculating the impression value. The calculation data for the estimated value is calculated by dividing the ray tracing method calculation results into five component surfaces: ceiling, side walls, floor, front wall, and window, and the luminance (logarithmic value) for each pixel. The geometric mean of was calculated. It is possible to develop and examine previous studies that the impression changes depending on the brightness of the walls and floors by dividing the structure. The composition plane was divided by a method of separately creating an image in which a portion other than the pixel position corresponding to the composition plane of each image was masked in black and multiplying this information when calculating the geometric mean. In addition, in the arithmetic average, when the luminance is partly conspicuous, the numerical value may be biased and a value different from the actual impression may be evaluated, but this can be reduced by using the geometric average.

(Creation of impression amount estimation formula)
In parallel with the execution of the window pattern simulation, an impression amount estimation formula was created from the results of the subject experiment. The estimation formula is created by performing multiple regression analysis. When creating the estimation formula, the objective variable is the number of impressions of the subject experiment, the explanatory variable is the geometric mean of the luminance of the five component surfaces of the ceiling, both side walls, the floor, the front wall, and the window. A value obtained by multiplying the ratio of pixels in the entire image of the surface was used.
Thus, the impression amount estimation formula shown in the above-described formula (1) is obtained.

In the above-described embodiment, the case where the direction from the viewpoint 20 on the front side of the paper to the back side of the paper is viewed has been described, but the present invention is not limited to this example. For example, the present invention can also be applied to the case where the right side of the drawing is viewed from the viewpoint 20 on the front side of the drawing, or the left side of the drawing.
Moreover, although embodiment mentioned above demonstrated the case where indoor space included the ceiling 1, the left side wall 2, the right side wall 3, the front wall 4, the floor 5, the window 11, and the illumination 13, it is not restricted to this example. . For example, the indoor space may include the ceiling 1, the left side wall 2, the right side wall 3, the front wall 4, the floor 5, and the lighting 13 except for the window 11.
In the above-described embodiment, the image generation unit 154 acquires the indoor space identification information, the indoor space information, and the date / time information from the acquisition unit 152, and uses the acquired indoor space information and the date / time information to acquire the date / time information. The case where the luminance image LI in which the image indicating the luminance is generated is generated on the ceiling 1, the left side wall 2, the right side wall 3, the front wall 4, the floor 5, and the window 11 in the room date and time is described. However, the present invention is not limited to this example. For example, the acquisition unit 152 acquires a captured image of a room input by the user, and outputs the acquired captured image of the room to the image generation unit 154. The image generation unit 154 may generate the luminance image LI from the captured image output by the acquisition unit 152.

  In the above-described embodiment, the calculation unit 158 uses the indoor space information and the date / time information to apply luminance to the ceiling 1, left side wall 2, right side wall 3, front wall 4, floor 5, and window 11 of the room. Although the case where the brightness image with the mark is created has been described, the present invention is not limited to this example. For example, the calculation unit 158 does not create a luminance image, but each of the ceiling luminance image 1a, the left side wall luminance image 2a, the right side wall luminance image 3a, the front wall luminance image 4a, the floor luminance image 5a, and the window luminance image 11a. It is also possible to calculate the number of pixels included in. Further, for example, the calculation unit 158 may calculate ceiling luminance information, side wall luminance information, front wall luminance information, floor luminance information, and window luminance information without creating a luminance image.

In the above-described embodiment, the calculation unit 158 is included in each of the ceiling luminance image 1a, the left side wall luminance image 2a, the right side wall luminance image 3a, the front wall luminance image 4a, the floor luminance image 5a, and the window luminance image 11a. Although the case where the geometric average of luminance is calculated has been described, the present invention is not limited to this example. For example, instead of the geometric mean of luminance, a brightness scale value or discomfort glare may be calculated.
In the above-described embodiment, the case where the estimated value of the impression amount is output from the output unit 164 has been described, but the present invention is not limited to this example. For example, the output unit 164 is configured to acquire predetermined information from one or both of the calculation unit 158 and the impression amount estimation unit 160, and based on the acquired predetermined information, a rendering image, glare image, brightness An image and a luminance image may be displayed.
Further, in the above-described embodiment, when the luminance image is divided into each part of the room and the information for each part of the room that enters a specific viewpoint from each part is calculated, Although the case where the structural surface of the room such as the left side wall, the right side wall, the front wall, the floor, and the window is applied has been described, it is not limited to this example. For example, in the estimated value of the impression amount shown in Expression (1), it is only necessary to include a portion having a larger value among the weights indicated by B, C, D, E, F, and G. Specifically, when the values of “E” that is the weight for the front wall luminance information, “F” that is the weight for the floor luminance information, and “G” that is the weight for the window luminance information are large, As each part, you may apply a front wall, a floor, and a window. In addition, when the values of “B” that is the weight for the ceiling luminance information, “E” that is the weight for the front wall luminance information, and “G” that is the weight for the window luminance information are large, Front walls, floors and windows may be applied.

Moreover, although embodiment mentioned above demonstrated the case where the shape of indoor space was a square pole, it is not restricted to this example. For example, the shape of the indoor space may be an L-shape formed by connecting two square pillars.
FIG. 8 is a diagram illustrating another example of the indoor space. 8 shows another room composed of a ceiling 10 (not shown) (shown in FIG. 9), a side wall 6, a side wall 7, a side wall 8, and a floor 9 on the right side wall 3 of the indoor space shown in FIG. It is the figure which looked at the indoor space which connected the space from the top.
FIG. 9 is a diagram illustrating another example of the configuration of the indoor space of a building. FIG. 9 is a diagram of the indoor space shown in FIG. 8 as viewed from the viewpoint 20 on the near side of the paper surface toward the back side of the paper surface. According to FIG. 9, when the indoor space shown in FIG. 8 is viewed from the viewpoint 20 on the near side of the page, the open side 3 b that is not a window exists on the back side of the right side wall 3. . It connects with other indoor space via this open part 3b. It is assumed that light is inserted into the opening 3b from illumination (not shown) attached to another indoor space. In addition, when there is a window in another indoor space, it is assumed that light is inserted from the window into the opening 3b. In this case, the above-described calculation is performed by regarding the open portion 3b as a side wall or a window. By configuring in this way, the present invention is not limited to the case where the shape of the indoor space is a quadrangular prism, and can be applied even if the shape of the indoor space is an L-shape.

(Summary)
According to the impression amount estimation apparatus 100 according to the present embodiment, input information including room illumination information and daylight information is acquired, a luminance image is generated based on the acquired input information, and the generated luminance image is The information is divided into information for each part of the room that enters a specific viewpoint from each part of the room. Then, based on the information for each part of the room and the weight for the information for each part of the room, the value indicating the impression amount is calculated, and based on the value indicating the impression amount obtained by the calculation, the room Estimate the impression amount for.

In this way, since the luminance image generated based on the input information is divided into information for each part of the room that enters a specific viewpoint from each part of the room, the luminance in life for each component surface such as each part of the room Can be easily grasped, so that it can be applied to space design.
Then, based on the information for each part of the room and the weight for the information for each part of the room, the value indicating the impression amount is calculated, and based on the value indicating the impression amount obtained by the calculation, the room The amount of impression can be estimated. That is, a subjective impression amount felt by a person can be estimated from a physical quantity such as luminance information. Compared to the case where the brightness of the indoor space is calculated as the average value of the focused space, it is possible to select materials, select colors, select windows, etc. for each component surface. The application is easy, and the impression amount of the indoor space can be easily estimated even when the design is changed for each configuration surface constituting the indoor space. Since the user can grasp the value indicating the digitized impression amount, the impression amount can be evaluated at a certain level regardless of the experience and sense of the interior advisor.

According to the impression amount estimation apparatus 100 according to the present embodiment, the generated luminance image is obtained from ceiling information that enters a specific viewpoint from the ceiling of the room, wall information that enters a specific viewpoint from the wall of the room, and floor of the room. The information can be divided into floor information entering a specific viewpoint and window information entering a specific viewpoint from a room window. The value indicating the impression amount based on the weighting for the ceiling information and the ceiling information, the weighting for the wall information and the wall information, the weighting for the floor information and the floor information, and the weighting for the window information and the window information. And the impression amount for the room can be estimated based on the value indicating the impression amount obtained by the calculation.
In this way, the brightness image generated based on the input information enters ceiling information that enters a specific viewpoint from the ceiling of the room, wall information that enters a specific viewpoint from the wall of the room, and enters a specific viewpoint from the floor of the room. Since it is divided into floor information and window information that enters the specific viewpoint from the window of the room, it is possible to easily grasp the level of luminance in daily life for each component surface such as the ceiling, wall, floor, and window. Can be applied to space design.
The value indicating the impression amount based on the weighting for the ceiling information and the ceiling information, the weighting for the wall information and the wall information, the weighting for the floor information and the floor information, and the weighting for the window information and the window information. And the impression amount for the room can be estimated based on the value indicating the impression amount obtained by the calculation. That is, a subjective impression amount felt by a person can be estimated from a physical quantity such as luminance information. Compared to the case where the brightness of the indoor space is calculated as the average value of the focused space, it is possible to select materials, select colors, select windows, etc. for each component surface. The application is easy, and the impression amount of the indoor space can be easily estimated even when the design is changed for each configuration surface constituting the indoor space. Since the user can grasp the value indicating the digitized impression amount, the impression amount can be evaluated at a certain level regardless of the experience and sense of the interior advisor.

  According to the impression amount estimation apparatus 100 according to the present embodiment, the geometric average of ceiling information, the geometric average of wall information, the geometric average of floor information, and the geometric average of window information are calculated, and the geometric average of ceiling information and wall information are calculated. Further, based on the geometric average of the floor information, the geometric average of the floor information, and the geometric average of the window information, the value indicating the impression amount is calculated, and the impression amount for the room is calculated based on the value indicating the impression amount obtained by the calculation. Can be estimated. That is, a subjective impression amount felt by a person can be estimated from a physical quantity such as luminance information. Compared to the case where the brightness of the indoor space is calculated as the average value of the focused space, it is possible to select materials, colors, windows, etc. The application is easy, and the impression amount of the indoor space can be easily estimated even when the design is changed for each configuration surface constituting the indoor space.

(Modification (Part 1))
When the impression amount estimation apparatus 100 according to the modification generates the brightness image LI, the impression amount estimation apparatus 100 generates a brightness image by processing the generated brightness image LI. The impression amount estimation apparatus 100 divides the generated brightness image into constituent surfaces such as a ceiling, a wall, a floor, and a window, and calculates information that enters a specific viewpoint from each constituent surface. As mentioned above, information that enters a specific viewpoint from the ceiling of the room is called “ceiling information”, and information that enters a specific viewpoint from the wall of the room is called “wall information”, and enters a specific viewpoint from the floor of the room. The information is called “floor information”, and the information that enters a specific viewpoint from the window is called “window information”. Then, the impression amount estimation device 100 indicates the impression amount of the room based on each of the ceiling information, the wall information, the floor information, and the window information and the weighting for each of the ceiling information, the wall information, the floor information, and the window information. Calculate the value. The impression amount estimation apparatus 100 outputs an estimation result of the impression amount for the room based on a value indicating the obtained impression amount by calculation.

As an example of the hardware configuration of the impression amount estimation apparatus 100 according to the modification, FIG. 2 can be applied.
FIG. 3 can be applied to the functional block diagram of the impression amount estimation apparatus 100 according to the modification. However, the image generation unit 154 generates a luminance image LI, performs discrete wavelet decomposition on the generated luminance image LI, and copes with the roughness of the spatial change for details calculated at each decomposition level. A brightness image BI is generated by applying weighting and performing wavelet synthesis based on the result. The image generation unit 154 outputs the image information of the generated brightness image BI to the division unit 156.

  The dividing unit 156 acquires image information of the brightness image BI from the image generating unit 154. The dividing unit 156 performs image processing on the acquired brightness image B1 so that the part of the ceiling 1, the part of the left side wall 2, the part of the right side wall 3, the part of the front wall 4, the part of the floor 5, and the window 11 are processed. Divide into parts. That is, the dividing unit 156 acquires the ceiling brightness image 1ab entering the specific viewpoint from the ceiling of the room by dividing the brightness image BI into the portion of the ceiling 1. In addition, the dividing unit 156 acquires the left side wall brightness image 2ab entering the specific viewpoint from the left side wall 2 of the room by dividing the brightness image BI into the left side wall 2 part. Further, the dividing unit 156 acquires the right side wall brightness image 3ab entering the specific viewpoint from the right side wall 3 of the room by dividing the brightness image LI into the right side wall 3 portion. Further, the dividing unit 156 acquires the front wall brightness image 4ab entering the specific viewpoint from the front wall 4 of the room by dividing the brightness image LI into the front wall 4 portions. In addition, the dividing unit 156 acquires the floor brightness image 5ab that enters a specific viewpoint from the floor 5 of the room by dividing the brightness image LI into portions of the floor 5. In addition, the dividing unit 156 acquires the window brightness image 11ab entering the specific viewpoint from the window 11 of the room by dividing the brightness image LI into the window 11 portions. As a display example of the brightness image, FIG. 5 can be applied.

The dividing unit 156 includes the image information of the ceiling brightness image 1ab, the image information of the left side wall brightness image 2ab, the image information of the right side wall brightness image 3ab, the image information of the front wall brightness image 4ab, and the floor brightness image 5ab. The image information and the window brightness image 11ab are output to the calculation unit 158.
The calculation unit 158 outputs the image information of the ceiling brightness image 1ab, the image information of the left side wall brightness image 2ab, the image information of the right side wall brightness image 3ab, and the image information of the front wall brightness image 4ab output from the dividing unit 156. And the image information of the floor brightness image 5ab and the window brightness image 11ab are acquired. The calculation unit 158 includes pixels included in each of the ceiling brightness image 1ab, the left side wall brightness image 2ab, the right side wall brightness image 3ab, the front wall brightness image 4ab, the floor brightness image 5ab, and the window brightness image 11ab. Calculate the number. The calculation unit 158 includes pixels included in each of the ceiling brightness image 1ab, the left side wall brightness image 2ab, the right side wall brightness image 3ab, the front wall brightness image 4ab, the floor brightness image 5ab, and the window brightness image 11ab. The calculation result of the number is associated with the indoor space identification information.

  Further, the calculation unit 158 performs the following operations on the ceiling brightness image 1ab, the left side wall brightness image 2ab, the right side wall brightness image 3ab, the front wall brightness image 4ab, the floor brightness image 5ab, and the window brightness image 11ab. The brightness (logarithmic value) for each pixel included in each brightness image is read, and the geometric average of the read brightness is calculated. Here, the geometric mean is obtained by taking the root of the product of the read brightness (or the nth root if the number is n). The calculation unit 158 calculates the geometric average of the brightness obtained from the ceiling brightness image 1ab, the calculation result of the geometric average of the brightness obtained from the left side wall brightness image 2ab, and the right side wall brightness image 3ab. The calculation result of the geometric average of the brightness obtained from the above, the calculation result of the geometric average of the brightness obtained from the front wall brightness image 4ab, and the calculation of the geometric average of the brightness obtained from the floor brightness image 5ab The result and the calculation result of the geometric mean of the brightness obtained from the window brightness image 11ab are associated with the indoor space identification information.

Hereinafter, the calculation result of the geometric average of the brightness obtained from the ceiling brightness image 1ab is the ceiling brightness information, the calculation result of the geometric average of the brightness obtained from the left side wall brightness image 2ab is the left side wall brightness information, The calculation result of the geometric mean of the brightness obtained from the right side wall brightness image 3ab is the right side wall brightness information, the calculation result of the geometric mean of the brightness obtained from the front wall brightness image 4ab is the front wall brightness information, The calculation result of the geometric mean of brightness obtained from the floor brightness image 5ab is referred to as floor brightness information, and the calculation result of the geometric mean of brightness obtained from the window brightness image 11ab is referred to as window brightness information.
The calculation unit 158 includes pixels included in each of the ceiling brightness image 1ab, the left side wall brightness image 2ab, the right side wall brightness image 3ab, the front wall brightness image 4ab, the floor brightness image 5ab, and the window brightness image 11ab. The number of pixels of the entire image is obtained by summing the calculation results of the numbers.

  The calculation unit 158 obtains the ceiling pixel ratio by dividing the number of pixels included in the ceiling brightness image 1ab by the number of pixels of all the images. In addition, the calculation unit 158 obtains the left side wall pixel ratio by dividing the number of pixels included in the left side wall brightness image 2ab by the number of pixels of all the images. In addition, the calculation unit 158 obtains the right side wall pixel ratio by dividing the number of pixels included in the right side wall brightness image 3ab by the number of pixels of all the images. In addition, the calculation unit 158 calculates the front wall pixel ratio by dividing the number of pixels included in the front wall brightness image 4ab by the number of pixels of all the images. In addition, the calculation unit 158 obtains the floor pixel ratio by dividing the number of pixels included in the floor brightness image 5ab by the number of pixels of all the images. In addition, the calculation unit 158 obtains the window pixel ratio by dividing the number of pixels included in the window brightness image 11ab by the number of pixels of the entire image.

  The calculating unit 158 calculates the ceiling pixel ratio, left side wall pixel ratio, right side wall pixel ratio, front wall pixel ratio, floor pixel ratio, and window pixel ratio, ceiling brightness information, left side wall brightness information, and right side wall brightness. By substituting the height information, the front wall brightness information, the floor brightness information, and the window brightness information into an impression amount estimation formula stored in the storage unit 162, a value indicating the impression amount is calculated. Specifically, the estimation formula for the impression amount is expressed by Expression (2). The derivation of the impression amount estimation formula will be described later.

  Estimated value of impression amount = AA + BA (ceiling brightness information × ceiling pixel ratio) + CA (left side wall brightness information × left side wall pixel ratio) + DA (right side wall brightness information × right side wall pixel ratio) + EA (front wall brightness information) X front wall pixel ratio) + FA (floor brightness information x floor pixel ratio) + GA (window brightness information x window pixel ratio) (2)

In Expression (2), AA, BA, CA, DA, EA, FA, and GA are real numbers, and are set in advance by the administrator of the impression amount estimation apparatus 100. AA is a constant, BA is a weight for ceiling brightness information, CA is a weight for left side wall brightness information, DA is a weight for right side wall brightness information, and EA is a weight for front wall brightness information. FA is a weight for floor brightness information, and GA is a weight for window brightness information.
In addition, AA, BA, CA, DA, EA, FA, and GA have an estimated impression amount that is a sense of openness, comfort, likes and dislikes, dazzling, calmness, brightness, cheerfulness, comfort, liveliness, or warmth. It takes different values depending on whether or not.
The calculation unit 158 outputs a value indicating the impression amount to the impression amount estimation unit 160.

(Operation of impression amount estimation device)
FIG. 6 can be applied to a flowchart showing an example of the operation of the impression amount estimation apparatus according to the modification. However, in step S104, when the image generation unit 154 acquires the input information output by the acquisition unit 152, the image generation unit 154 generates a luminance image LI using the indoor space information and date / time information included in the acquired input information. Furthermore, the image generation unit 154 creates a brightness image BI based on the created brightness image LI.
In step S106, the dividing unit 156 converts the brightness image BI into a ceiling brightness image 1ab, a left side wall brightness image 2ab, a right side wall brightness image 3ab, a front wall brightness image 4ab, a floor brightness image 5ab, and a window. The image is divided into brightness images 11ab.
In step S108, the calculation unit 158 includes each of the ceiling brightness image 1ab, the left side wall brightness image 2ab, the right side wall brightness image 3ab, the front wall brightness image 4ab, the floor brightness image 5ab, and the window brightness image 11ab. The number of pixels contained in is calculated. The calculation unit 158 includes pixels included in each of the ceiling brightness image 1ab, the left side wall brightness image 2ab, the right side wall brightness image 3ab, the front wall brightness image 4ab, the floor brightness image 5ab, and the window brightness image 11ab. The calculation result of the number is associated with the indoor space identification information.

The computing unit 158 is included in each of the ceiling brightness image 1ab, the left side wall brightness image 2ab, the right side wall brightness image 3ab, the front wall brightness image 4ab, the floor brightness image 5ab, and the window brightness image 11ab. By reading the brightness for each pixel and calculating the geometric average of the read brightness, ceiling brightness information, left side wall brightness information, right side wall brightness information, front wall brightness information, floor brightness information, And window brightness information.
The calculation unit 158 includes pixels included in each of the ceiling brightness image 1ab, the left side wall brightness image 2ab, the right side wall brightness image 3ab, the front wall brightness image 4ab, the floor brightness image 5ab, and the window brightness image 11ab. From the calculation results of the numbers, a ceiling pixel ratio, a left side wall pixel ratio, a right side wall pixel ratio, a front wall pixel ratio, a floor pixel ratio, and a window pixel ratio are calculated. The calculation unit 158 substitutes each pixel ratio, ceiling brightness information, side wall brightness information, front wall brightness information, floor brightness information, and window brightness information into an impression amount estimation formula, thereby obtaining an impression. A value indicating the quantity is calculated.

(Summary)
According to the impression amount estimation device 100 according to the modification, the brightness image generated from the luminance image can be divided into information for each part of the room that enters the specific viewpoint from each part of the room.
In this way, the brightness image generated from the luminance image is divided into information for each part of the room that enters the specific viewpoint from each part of the room, so that design is performed for each component surface such as each part of the room be able to.
According to the impression amount estimation apparatus 100 according to the modified example, the brightness information generated from the luminance image includes ceiling information that enters a specific viewpoint from the ceiling of the room, wall information that enters a specific viewpoint from the wall of the room, and the room It can be divided into floor information entering a specific viewpoint from the floor of the room and window information entering a specific viewpoint from the window of the room.
In this way, the brightness image generated from the luminance image has ceiling information that enters a specific viewpoint from the ceiling of the room, wall information that enters a specific viewpoint from the wall of the room, and a floor that enters a specific viewpoint from the floor of the room. Since it is divided into information and window information that enters the specific viewpoint from the window of the room, it is possible to design for each component surface such as a ceiling, a wall, a floor, and a window.
According to the impression amount estimation apparatus 100 according to the modification, the geometric average of the ceiling information, the geometric average of the wall information, the geometric average of the floor information, and the geometric average of the window information are calculated, and the geometric average of the ceiling information and the wall information Further, based on the geometric average, the geometric average of the floor information, and the geometric average of the window information, the value indicating the impression amount is calculated, and the impression amount for the room is calculated based on the value indicating the impression amount obtained by the calculation. Can be estimated. That is, a subjective impression amount felt by a person can be estimated from a physical quantity such as luminance information. Compared to the case where the brightness of the indoor space is calculated as the average value of the focused space, it is possible to select materials, colors, windows, etc. The application is easy, and the impression amount of the indoor space can be easily estimated even when the design is changed for each configuration surface constituting the indoor space.

(Modification (Part 2))
When the impression amount estimation apparatus 100 according to the modification generates the luminance image LI, the impression amount estimation apparatus 100 generates the glare image GI by processing the generated luminance image LI. The impression amount estimation apparatus 100 divides the generated glare image GI into component surfaces such as a ceiling, a wall, a floor, and a window, and calculates information that enters a specific viewpoint from each component surface. As mentioned above, information that enters a specific viewpoint from the ceiling of the room is called “ceiling information”, and information that enters a specific viewpoint from the wall of the room is called “wall information”, and enters a specific viewpoint from the floor of the room. The information is called “floor information”, and the information that enters a specific viewpoint from the window is called “window information”. Then, the impression amount estimation device 100 indicates the impression amount of the room based on each of the ceiling information, the wall information, the floor information, and the window information and the weighting for each of the ceiling information, the wall information, the floor information, and the window information. Calculate the value. The impression amount estimation apparatus 100 outputs an estimation result of the impression amount for the room based on a value indicating the obtained impression amount by calculation.

As an example of the hardware configuration of the impression amount estimation apparatus 100 according to the modification, FIG. 2 can be applied.
FIG. 3 can be applied to the functional block diagram of the impression amount estimation apparatus 100 according to the modification. However, the image generation unit 154 generates a luminance image LI, and multiplies an image derived by performing wavelet analysis on the generated luminance image LI with human perception characteristics related to glare obtained from an experiment. Thus, the glare image GI is generated. The image generation unit 154 outputs the image information of the generated glare image GI to the division unit 156.
The dividing unit 156 acquires image information of the glare image GI from the image generating unit 154. The dividing unit 156 performs image processing on the acquired glare image B1, thereby performing a ceiling 1 part, a left side wall 2 part, a right side wall 3 part, a front wall 4 part, a floor 5 part, and a window 11 part. Divide into That is, the dividing unit 156 acquires the ceiling glare image 1ac that enters the specific viewpoint from the ceiling of the room by dividing the glare image GI into the portion of the ceiling 1. Further, the dividing unit 156 acquires the left-side wall glare image 2ac that enters a specific viewpoint from the left-side wall 2 of the room by dividing the glare image GI into portions of the left-side wall 2. Further, the dividing unit 156 acquires the right side wall glare image 3ac that enters the specific viewpoint from the right side wall 3 of the room by dividing the glare image GI into the right side wall 3 portions. Further, the dividing unit 156 acquires the front wall glare image 4ac entering the specific viewpoint from the front wall 4 of the room by dividing the glare image GI into the front wall 4 portions. Further, the dividing unit 156 acquires the floor glare image 5ac that enters a specific viewpoint from the floor 5 of the room by dividing the glare image GI into portions of the floor 5. Further, the dividing unit 156 obtains a window glare image 11ac that enters a specific viewpoint from the window 11 of the room by dividing the glare image GI into portions of the window 11. FIG. 5 can be applied as a display example of the glare image.

The dividing unit 156 includes image information of the ceiling glare image 1ac, image information of the left side wall glare image 2ac, image information of the right side wall glare image 3ac, image information of the front wall glare image 4ac, image information of the floor glare image 5ac, and window glare. The image 11ac is output to the calculation unit 158.
The calculation unit 158 outputs the image information of the ceiling glare image 1ac, the image information of the left side wall glare image 2ac, the image information of the right side wall glare image 3ac, the image information of the front wall glare image 4ac, and the floor glare image output from the dividing unit 156. Image information of 5ac and window glare image 11ac are acquired. The calculation unit 158 calculates the number of pixels included in each of the ceiling glare image 1ac, the left side wall glare image 2ac, the right side wall glare image 3ac, the front wall glare image 4ac, the floor glare image 5ac, and the window glare image 11ac. The calculation unit 158 calculates the calculation result of the number of pixels included in each of the ceiling glare image 1ac, the left side wall glare image 2ac, the right side wall glare image 3ac, the front wall glare image 4ac, the floor glare image 5ac, and the window glare image 11ac. Associate with indoor space identification information.

Further, the calculation unit 158 includes a ceiling glare image 1ac, a left side wall glare image 2ac, a right side wall glare image 3ac, a front wall glare image 4ac, a floor glare image 5ac, and a window glare image 11ac in each glare image. Calculate the maximum glare value. For example, the calculation unit 158 calculates the maximum glare value due to daylight from the Glare Index (GI), the British Day light Glare Index (BGI), the CIE Glare Index (CGI), the Predicted Glare Sensation vote (PGS) evaluation method, etc. Use to calculate. In addition, the calculation unit 158 may calculate a value calculated from an evaluation method such as GI, BGI, CGI, PGSV, etc., using a value converted into a unified glare rating (UGR). The calculation unit 158 includes a maximum glare value obtained from the ceiling glare image 1ac, a maximum glare value obtained from the left side wall glare image 2ac, a maximum glare value obtained from the right side wall glare image 3ac, The maximum glare value obtained from the wall glare image 4ac, the maximum glare value obtained from the floor glare image 5ac, and the maximum glare value obtained from the window glare image 11ac are associated with the indoor space identification information.
Hereinafter, the maximum glare value obtained from the ceiling glare image 1ac is the ceiling glare information, the maximum glare value obtained from the left side wall glare image 2ac is the left side wall glare information, and the maximum glare value obtained from the right side wall glare image 3ac. The value is obtained from the right side wall glare information, the maximum glare value obtained from the front wall glare image 4ac is obtained from the front wall glare information, and the maximum glare value obtained from the floor glare image 5ac is obtained from the floor glare information and the window glare image 11ac. The maximum glare value is called window glare information.

  The computing unit 158 substitutes the ceiling glare information, left side wall glare information, right side wall glare information, front wall glare information, floor glare information, and window glare information into the impression amount estimation formula stored in the storage unit 162. Thus, a value indicating the impression amount is calculated. Specifically, the estimation formula for the impression amount is expressed by Expression (3). The derivation of the impression amount estimation formula will be described later.

  Estimated impression amount = AC + BC (ceiling glare information) + CC (left side wall glare information) + DC (right side wall glare information) + EC (front wall glare information) + FC (floor glare information) + GC (window glare information) (3)

In Expression (3), AC, BC, CC, DC, EC, FC, and GC are real numbers, and are set in advance by the administrator of the impression amount estimation apparatus 100. AC is a constant, BC is a weight for ceiling glare information, CC is a weight for left side wall glare information, DC is a weight for right side wall glare information, EC is a weight for front wall glare information, FC Is a weight for floor glare information, and GC is a weight for window glare information.
For AC, BC, CC, DC, EC, FC, and GC, the estimated amount of impression is an open feeling, a feeling of comfort, dislikes, dazzling, calmness, brightness, cheerfulness, comfort, liveliness, or warmth It takes different values depending on whether or not.
The calculation unit 158 outputs a value indicating the impression amount to the impression amount estimation unit 160.

(Operation of impression amount estimation device)
FIG. 6 can be applied to a flowchart showing an example of the operation of the impression amount estimation apparatus according to the modification. However, in step S104, when the image generation unit 154 acquires the input information output by the acquisition unit 152, the image generation unit 154 generates a luminance image LI using the indoor space information and date / time information included in the acquired input information. Furthermore, the image generation unit 154 creates a glare image GI based on the created luminance image LI.
In step S106, the dividing unit 156 divides the glare image GI into a ceiling glare image 1ac, a left side wall glare image 2ac, a right side wall glare image 3ac, a front wall glare image 4ac, a floor glare image 5ac, and a window glare image 11ac. .
In step S108, the calculation unit 158 calculates the maximum values of the ceiling glare image 1ac, the left side wall glare image 2ac, the right side wall glare image 3ac, the front wall glare image 4ac, the floor glare image 5ac, and the window glare image 11ac. . The calculation unit 158 identifies the maximum value included in each of the ceiling glare image 1ac, the left side wall glare image 2ac, the right side wall glare image 3ac, the front wall glare image 4ac, the floor glare image 5ac, and the window glare image 11ac in the indoor space. Associate with information.

In addition, the calculation unit 158 includes the ceiling glare image 1ac, the left side wall glare image 2ac, the right side wall glare image 3ac, the front wall glare image 4ac, the floor glare image 5ac, and the window glare image 11ac. Reading, ceiling glare information, left side wall glare information, right side wall glare information, front wall glare information, floor glare information, and window glare information are calculated. The maximum value included in each of the image 3ac, the front wall glare image 4ac, the floor glare image 5ac, and the window glare image 11ac is calculated. The calculation unit 158 calculates a value indicating the impression amount by substituting the ceiling glare information, the side wall glare information, the front wall glare information, the floor glare information, and the window glare information into the impression amount estimation formula.
In the modified example described above, the calculation unit 158 has the maximum glare value obtained from the ceiling glare image 1ac, the maximum glare value obtained from the left side wall glare image 2ac, and the glare obtained from the right side wall glare image 3ac. The maximum glare value obtained from the front wall glare image 4ac, the maximum glare value obtained from the floor glare image 5ac, and the maximum glare value obtained from the window glare image 11ac. Although the case of associating with the space identification information has been described, the present invention is not limited to this example. For example, instead of using the maximum glare value, the glare threshold value (evaluation point) in question may be associated with the indoor space identification information. Here, when the value proposed by the used evaluation method is used as the threshold, for example, a value “22” that starts to feel uncomfortable with a value converted to UGR may be used as the threshold. When other evaluation methods are used, the threshold value may be a value at which the user begins to feel uncomfortable.

(Summary)
According to the impression amount estimation apparatus 100 according to the modification, the glare image generated from the luminance image can be divided into information for each part of the room that enters the specific viewpoint from each part of the room.
In this way, since the glare image generated from the luminance image is divided into information for each part of the room that enters the specific viewpoint from each part of the room, design is performed for each component surface such as each part of the room Can do.
According to the impression amount estimation apparatus 100 according to the modified example, the glare image generated from the luminance image is obtained by using ceiling information that enters a specific viewpoint from the ceiling of the room, wall information that enters a specific viewpoint from the wall of the room, It can be divided into floor information entering a specific viewpoint from the floor and window information entering a specific viewpoint from the window of the room.
In this way, the glare image generated from the luminance image has ceiling information that enters a specific viewpoint from the ceiling of the room, wall information that enters a specific viewpoint from the wall of the room, and floor information that enters a specific viewpoint from the floor of the room And window information entering the specific viewpoint from the window of the room, the design can be performed for each component surface such as a ceiling, a wall, a floor, and a window.

  According to the impression amount estimation apparatus 100 according to the modification, the maximum value of the ceiling information, the maximum value of the wall information, the maximum value of the floor information, and the maximum value of the window information are calculated, and the maximum value of the ceiling information and the wall information Further, based on the maximum value, the maximum value of floor information, and the maximum value of window information, the value indicating the impression amount is calculated, and the impression amount for the room is calculated based on the value indicating the impression amount obtained by the calculation. Can be estimated. That is, a subjective impression amount felt by a person can be estimated from a physical quantity such as luminance information. Discomfort due to glare in the indoor space can be evaluated for each component surface, so it is easy to determine if glare is a problem on the side where the line of sight is easily directed, so it can be easily applied to space design and Even when the design is changed for each component surface constituting the space, the impression amount of the indoor space can be easily estimated.

(Modification (Part 3))
In the embodiment described above, the impression amount estimation apparatus 200 according to the modification stores the luminance image LI described above in association with the indoor space identification information. For example, the luminance image LI is generated by using a radiosity method, a ray tracing method, or the like, and is stored in the impression amount estimation apparatus 200 by the administrator.
When the impression amount estimation device 200 according to the modification acquires the indoor space identification information input by the user of the impression amount estimation device 200, the impression amount estimation device 200 acquires the luminance image LI stored in association with the acquired indoor space identification information. The impression amount estimation apparatus 200 divides the acquired luminance image LI into a ceiling 1 part, a left side wall 2 part, a right side wall 3 part, a front wall 4 part, a floor 5 part, and a window 11 part. Thus, the ceiling luminance image 1a, the left side wall luminance image 2a, the right side wall luminance image 3a, the front wall luminance image 4a, the floor luminance image 5a, and the window luminance image 11a are acquired.

  The impression amount estimation apparatus 200 calculates the number of pixels included in each acquired luminance image. The impression amount estimation apparatus 200 calculates ceiling luminance information, left side wall luminance information, right side wall luminance information, front wall luminance information, floor luminance information, and window luminance information from each of the acquired luminance images. The impression amount estimation apparatus 200 according to the modified example calculates the impression amount from the calculation result of the number of pixels and the ceiling luminance information, left side wall luminance information, right side wall luminance information, front wall luminance information, floor luminance information, and window luminance information. Is calculated, and the impression amount is estimated based on the value indicating the impression amount obtained by the calculation.

FIG. 2 can be applied to the hardware configuration of the impression amount estimation apparatus 200 according to the modification.
(Functional structure of impression amount estimation device)
FIG. 10 is a functional block diagram of an impression amount estimation apparatus according to a modification.
The impression amount estimation apparatus 200 outputs the acquisition unit 252, the division unit 256, the calculation unit 258, the impression amount estimation unit 260, the storage unit 262, and the output by causing the CPU 102 to execute a program developed on the RAM 106 from the auxiliary storage device 112. It functions as the unit 264.

(Each functional configuration of impression amount estimation device)
Each functional configuration of the impression amount estimation apparatus 200 will be described in detail with reference to FIGS. 2 and 10. In the following, in describing each function of the impression amount estimation apparatus 200, a relationship with main hardware for realizing each functional block of the impression amount estimation apparatus 200 shown in FIG. 10 will also be described.

  The acquisition unit 252 can apply the acquisition unit 152 described above. However, the acquisition unit 252 acquires input information input by the user from the input / output device 108. The input information includes indoor space identification information. When the impression amount estimation device 100 is activated, a screen for inputting the indoor space identification information is displayed on the input / output device 108. The user inputs the indoor space identification information of the indoor space for which the impression amount is to be estimated on the screen for inputting the indoor space identification information. The acquisition unit 252 outputs the indoor space identification information input by the user operating the input / output device 108 to the impression amount estimation unit 260.

The dividing unit 256 can apply the dividing unit 156 described above. However, when the dividing unit 256 acquires the indoor space identification information output by the acquisition unit 252, the dividing unit 256 acquires the luminance image LI associated with the acquired indoor space identification information from the storage unit 262.
The dividing unit 256 performs image processing on the acquired luminance image LI, thereby performing a ceiling 1 part, a left side wall 2 part, a right side wall 3 part, a front wall 4 part, a floor 5 part, and a window 11 part. By dividing into two, the ceiling luminance image 1a, the left side wall luminance image 2a, the right side wall luminance image 3a, the front wall luminance image 4a, the floor luminance image 5a, and the window luminance image 11a are obtained.
The calculation unit 258 can apply the calculation unit 158 described above. However, the calculation unit 258 calculates the number of pixels included in each of the ceiling luminance image 1a, the left side wall luminance image 2a, the right side wall luminance image 3a, the front wall luminance image 4a, the floor luminance image 5a, and the window luminance image 11a. . Further, the calculation unit 258 obtains the number of pixels of the entire image by summing the calculation results of the number of pixels included in each luminance image.

  The calculation unit 258 calculates the ceiling pixel ratio by dividing the number of pixels included in the ceiling luminance image 1a by the number of pixels of all the images. In addition, the calculation unit 258 obtains the left side wall pixel ratio by dividing the number of pixels included in the left side wall luminance image 2a by the number of pixels of the entire image. In addition, the calculation unit 258 obtains the right side wall pixel ratio by dividing the number of pixels included in the right side wall luminance image 3a by the number of pixels of the entire image. In addition, the calculation unit 258 calculates the front wall pixel ratio by dividing the number of pixels included in the front wall luminance image 4a by the number of pixels of all the images. In addition, the calculation unit 258 obtains the floor pixel ratio by dividing the number of pixels included in the floor luminance image 5a by the number of pixels of all the images. In addition, the calculation unit 258 obtains the window pixel ratio by dividing the number of pixels included in the window luminance image 11a by the number of pixels of the entire image.

Furthermore, the calculation unit 258 includes the ceiling luminance image 1a, the left side wall luminance image 2a, the right side wall luminance image 3a, the front wall luminance image 4a, the floor luminance image 5a, and the window luminance image 11a in each luminance image. By reading the luminance for each pixel and calculating the geometric average of the read luminances, ceiling luminance information, left side wall luminance information, right side wall luminance information, front wall luminance information, floor luminance information, and window luminance information are obtained.
The calculation unit 258 includes a ceiling pixel ratio, a left side wall pixel ratio, a right side wall pixel ratio, a front wall pixel ratio, a floor pixel ratio, and a window pixel ratio, a ceiling luminance information, a left side wall luminance information, a right side wall luminance information, and a front wall. By substituting the luminance information, the floor luminance information, and the window luminance information into Expression (1) that is an estimation expression of the impression amount stored in the storage unit 262, a value indicating the impression amount is calculated.

The impression amount estimation unit 260 can apply the impression amount estimation unit 160 described above. However, the impression amount estimation unit 260 estimates the impression amount based on the value indicating the impression amount output from the calculation unit 158. The impression amount estimation unit 260 outputs the impression amount estimation result to the output unit 264.
The storage unit 162 described above can be applied to the storage unit 262. The storage unit 262 stores an impression amount estimation formula. In addition, the storage unit 262 stores the luminance image LI in association with the indoor space identification information.
The output unit 264 can be the output unit 164 described above. The output unit 264 outputs the impression amount estimation result acquired from the impression amount estimation unit 260. Specifically, the output unit 264 outputs the estimation result of the impression amount, the evaluation value of the feeling of openness, the evaluation value of the feeling of comfort, or the evaluation value of likes and dislikes to the input / output device 108 such as a display, or the communication module 110. Or output to other devices via

(Operation of impression amount estimation device)
FIG. 11 is a flowchart illustrating an example of the operation of the impression amount estimation apparatus according to the modification.
(Step S <b> 202) The acquisition unit 252 acquires input information input by the user operating the input / output device 108. The acquiring unit 252 outputs the acquired input information to the dividing unit 256. As described above, the input information includes the indoor space identification information.
(Step S204) When the division unit 256 acquires the input information output by the acquisition unit 252, the luminance associated with the indoor space information from the storage unit 262 using the indoor space information included in the acquired input information. An image LI is acquired.

(Step S206) The dividing unit 256 divides the luminance image LI into a ceiling luminance image 1a, a left side wall luminance image 2a, a right side wall luminance image 3a, a front wall luminance image 4a, a floor luminance image 5a, and a window luminance image 11a. .
(Step S208) The computing unit 258 calculates the number of pixels included in each of the ceiling luminance image 1a, the left side wall luminance image 2a, the right side wall luminance image 3a, the front wall luminance image 4a, the floor luminance image 5a, and the window luminance image 11a. Calculate.
The computing unit 258 also calculates the luminance for each pixel included in each of the ceiling luminance image 1a, left side wall luminance image 2a, right side wall luminance image 3a, front wall luminance image 4a, floor luminance image 5a, and window luminance image 11a. By reading and calculating the geometric average of the read luminances, ceiling luminance information, left side wall luminance information, right side wall luminance information, front wall luminance information, floor luminance information, and window luminance information are obtained.
The calculation unit 258 calculates the number of pixels included in each of the ceiling luminance image 1a, the left side wall luminance image 2a, the right side wall luminance image 3a, the front wall luminance image 4a, the floor luminance image 5a, and the window luminance image 11a. The ceiling pixel ratio, left side wall pixel ratio, right side wall pixel ratio, front wall pixel ratio, floor pixel ratio, and window pixel ratio are calculated. The calculation unit 258 uses each pixel ratio, ceiling luminance information, left side wall luminance information, left side wall luminance information, front wall luminance information, floor luminance information, and window luminance information as an expression (1) ) To calculate a value indicating the impression amount. The calculation unit 258 outputs a value indicating the impression amount to the impression amount estimation unit 260.
(Step S210) The impression amount estimation unit 160 estimates the impression amount based on the value indicating the impression amount output by the calculation unit 158.

In the present modification, the case where the impression amount estimation apparatus 200 stores the luminance image LI in association with the indoor space identification information has been described, but the present invention is not limited to this example. For example, the brightness image BI may be stored in association with the indoor space identification information, or the glare image GI may be stored.
According to the impression amount estimation apparatus 200 according to the modification, the luminance image LI is stored in association with the indoor space identification information. Thus, when the impression amount estimation device 200 according to the modification acquires the indoor space identification information input by the user of the impression amount estimation device 200, the impression amount estimation device 200 is based on the luminance image LI stored in association with the acquired indoor space identification information. Thus, the impression amount can be estimated. That is, according to the impression amount estimation apparatus 200 according to the modified example, it is possible to refer to the impression amount estimation result by storing the luminance image LI in association with the indoor space identification information. .

The embodiments and the modifications thereof have been described above. However, these embodiments and the modifications thereof are presented as examples, and are not intended to limit the scope of the invention. These embodiments and modifications thereof can be implemented in various other forms, and various omissions, replacements, changes, and combinations can be made without departing from the spirit of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and at the same time, are included in the invention described in the claims and the equivalents thereof. For example, an impression amount estimation method executed by an impression amount estimation device or a computer device can be realized as a building design method executed by a computer device.
For example, in the embodiment and the modification thereof, the case where the front wall is visible when the indoor space of the building is viewed from the viewpoint 20 is described, but the present invention is not limited to this example. For example, the present invention can be applied to a case where the front wall is not visible when the indoor space of a building is viewed.
FIG. 12 is a diagram illustrating an example of the configuration of the indoor space of a building. The example shown in FIG. 12 shows a case where the front wall cannot be seen when viewing the indoor space of the building from the viewpoint 20. Even in such a case, the impression amount can be estimated by setting constituent surfaces such as a ceiling, a floor, both side walls, and a window, as in the above-described embodiment and its modifications.

Note that the impression amount estimation apparatus 100 and the impression amount estimation apparatus 200 described above are realized by a computer as described above. In this case, a program for realizing the function of each functional block is recorded on a computer-readable recording medium. The program recorded on the recording medium may be read by a computer system and executed by the CPU. The “computer system” here includes hardware such as an OS (Operating System) and peripheral devices.
The “computer-readable recording medium” refers to a portable medium such as a flexible disk, a magneto-optical disk, a ROM, and a CD-ROM. The “computer-readable recording medium” includes a storage device such as a hard disk built in the computer system.

Furthermore, the “computer-readable recording medium” may include a medium that dynamically holds a program for a short time. What holds the program dynamically for a short time is, for example, a communication line when the program is transmitted via a network such as the Internet or a communication line such as a telephone line.
In addition, the “computer-readable recording medium” may include a medium that holds a program for a certain period of time, such as a volatile memory inside a computer system that serves as a server or a client.
The program may be for realizing a part of the functions described above. Further, the program may be a program that can realize the above-described functions in combination with a program already recorded in the computer system.
The program may be realized using a programmable logic device. The programmable logic device is, for example, an FPGA (Field Programmable Gate Array).

The impression amount estimation apparatus 100 and the impression amount estimation apparatus 200 described above have a computer inside. Each process of the impression amount estimation apparatus 100 described above is stored in a computer-readable recording medium in the form of a program, and the above process is performed by the computer reading and executing the program. Here, the computer-readable recording medium means a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD-ROM, a semiconductor memory, or the like. Alternatively, the computer program may be distributed to the computer via a communication line, and the computer that has received the distribution may execute the program.
The program may be for realizing a part of the functions described above.
Furthermore, what can implement | achieve the function mentioned above in combination with the program already recorded on the computer system, what is called a difference file (difference program) may be sufficient.

DESCRIPTION OF SYMBOLS 1,10 ... Ceiling, 1a ... Ceiling luminance image, 2 ... Left side wall, 2a ... Left side wall luminance image, 2ab ... Left side wall brightness image, 2ac ... Left side wall glare image, 3 ... Right side wall, 3a ... Right side wall luminance image 3ab ... right side wall brightness image, 3ac ... right side wall glare image, 3b ... open part, 4 ... front wall, 4a ... front wall brightness image, 4ab ... front wall brightness image, 4ac ... front wall glare image, 5, 9 ... Floor, 5a ... Floor brightness image, 5ab ... Floor brightness image, 5ac ... Floor glare image, 6, 7, 8 ... Side wall, 11 ... Window, 11a ... Window brightness image, 11ab ... Window brightness image, 11ac ... Window glare image, 13 ... Illumination, 20 ... Viewpoint, 100, 200 ... Impression amount estimation device, 102 ... CPU, 104 ... ROM, 106 ... RAM, 108 ... I / O device, 110 ... Communication module, 112 ... Auxiliary storage device 1 DESCRIPTION OF SYMBOLS 20 ... Bus, 152, 252 ... Acquisition part, 154 ... Image generation part, 156, 256 ... Dividing part, 158, 258 ... Calculation part, 160, 260 ... Impression amount estimation part, 162, 262 ... Storage part, 164, 264 ... Output unit, 170 ... Input screen

Claims (10)

An impression amount estimation method for estimating an impression amount for a room recognized from a specific viewpoint using a computer device,
Obtaining input information including room lighting information and daylight information;
Generating a luminance image based on the input information;
Dividing the luminance image into information for each part of the room entering the specific viewpoint from each part of the room;
And calculating a value indicating an impression amount based on information for each part of the room and weighting for information for each part of the room. In the dividing step, the luminance image is converted into ceiling information that enters the specific viewpoint from the ceiling of the room, wall information that enters the specific viewpoint from the wall of the room, and the specific viewpoint from the floor of the room. Divided into floor information entering and window information entering the specific viewpoint from the window of the room,
In the calculating step, weighting for the ceiling information and the ceiling information, weighting for the wall information and the wall information, weighting for the floor information and the floor information, and weighting for the window information and the window information. The impression amount estimation method according to claim 1, wherein a value indicating an impression amount is calculated based on the impression amount. Generating a brightness image from the brightness image generated in the step of generating the brightness image,
The impression amount estimation method according to claim 1, wherein in the dividing step, the brightness image is divided into information for each part of the room entering the specific viewpoint from each part of the room. In the dividing step, the brightness image is converted from the ceiling information that enters the specific viewpoint from the ceiling of the room, the wall information that enters the specific viewpoint from the wall of the room, and the specific image from the floor of the room. Dividing into floor information entering the viewpoint and window information entering the specific viewpoint from the window of the room,
In the calculating step, weighting for the ceiling information and the ceiling information, weighting for the wall information and the wall information, weighting for the floor information and the floor information, and weighting for the window information and the window information. The impression amount estimation method according to claim 3, wherein a value indicating an impression amount is calculated based on the impression amount.   In the calculating step, a geometric average of the ceiling information, a geometric average of the wall information, a geometric average of the floor information, and a geometric average of the window information are calculated, and the geometric average of the ceiling information and the geometric information of the wall information are calculated. The impression amount estimation method according to claim 2, wherein the calculation is further performed based on an average, a geometric average of the floor information, and a geometric average of the window information. Generating a glare image from the luminance image generated in the step of generating the luminance image,
The impression amount estimation method according to claim 1, wherein in the dividing step, the glare image is divided into information for each part of the room entering the specific viewpoint from each part of the room.   In the dividing step, the glare image is obtained by adding ceiling information that enters the specific viewpoint from the ceiling of the room, wall information that enters the specific viewpoint from the wall of the room, and the specific viewpoint from the floor of the room. The impression amount estimation method according to claim 6, wherein the impression information is divided into floor information entering and window information entering the specific viewpoint from the window of the room.   In the calculating step, the maximum value of the ceiling information, the maximum value of the wall information, the maximum value of the floor information, and the maximum value of the window information are calculated, and the maximum value of the ceiling information and the maximum value of the wall information are calculated. The impression amount estimation method according to claim 7, wherein the calculation is further performed based on a value, a maximum value of the floor information, and a maximum value of the window information. An impression amount estimation device for estimating an impression amount for a room recognized from a specific viewpoint,
An acquisition unit for acquiring input information including room lighting information and daylight information;
A generating unit that generates a luminance image based on the input information;
A dividing unit that divides the luminance image into information for each part of the room entering the specific viewpoint from each part of the room;
An impression amount estimation apparatus comprising: a calculation unit that calculates a value indicating an impression amount based on information for each part of the room and weighting for information for each part of the room.   A building design method using the impression amount estimation method according to any one of claims 1 to 8.

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