JP2019061665A - Image processing system, control method thereof, and program - Google Patents

Abstract

To provide a mechanism capable of calculating the number of people who have passed a predetermined position from an image and calculating the number of people suitable for the purpose. An image processing system includes an acquisition unit that acquires a plurality of images in which a person is photographed, a counting unit that counts the number of persons in the image who have passed a predetermined position, and the image And a passing direction acquisition means for acquiring passing direction information indicating a passing direction in which the person who has passed through the predetermined position passes through the predetermined position based on the passing direction information acquired by the passing direction acquisition means. A counting exclusion means for determining whether or not the counted person is a count exclusion target excluded from the counting of the number of people by the counting means, and the counting means is the count exclusion target by the count exclusion means If determined, the number of persons determined to be excluded from the count is excluded from the count. [Selection] Figure 1

Description

  The present invention relates to an image processing system, a control method of the image processing system, and a program.

  In recent years, a system for counting the number of people using video of a network camera has been proposed. For example, Patent Document 1 proposes a mechanism for calculating the number of people according to the number of faces in the captured image by acquiring the captured image output from the camera and performing face recognition on the captured image. ing.

  Further, Patent Document 2 proposes a mechanism for photographing a specific part and performing image processing on the photographed image to count the number of people who have passed the specific part.

JP, 2011-221906, A JP 2008-217205 A

  Analyzing the image (video) of the network camera using the mechanisms of Patent Document 1 and Patent Document 2 to calculate the number of people appearing in the image and the number of people passing through the predetermined position Can.

  However, when using the technology proposed in these patent documents, for example, when it is desired to count the number of people who have participated in the event hall, etc., even people who are not participants of the event will be counted. .

  In addition, there is also a problem that it is not possible to calculate the stay time for each user because people who stay for a long time and people who stay only for a short time are counted similarly.

  In addition, when the same user is counted many times, there is also a problem that the correct number of people can not be calculated when it is desired to count the actual number of people.

  Therefore, in view of these problems, it is an object of the present invention to provide a mechanism capable of calculating the number of persons suitable for the purpose when calculating the number of persons who have passed a predetermined position from an image.

  The image processing system according to the present invention is an image processing system capable of counting the number of persons who have passed a predetermined position, and an acquisition unit for acquiring a plurality of images in which a person is photographed, and an image processing system A counting means for counting the number of persons who are persons who have passed a predetermined position, a passing direction acquiring means for acquiring passing direction information indicating a passing direction in which the person shown in the image has passed the predetermined position, Count exclusion means for determining whether a person who has passed a predetermined position is a target for exclusion from the count of the number of people by the count means based on the passing direction information acquired by the acquisition means; If the means is determined by the count exclusion means to be count exclusion target, does the means count the number of persons determined to be count exclusion targets? Excluded.

  A control method of an image processing system according to the present invention is a control method of an image processing system that counts the number of persons who have passed a predetermined position, and an acquisition step of acquiring a plurality of images in which a person is photographed; A counting step for counting the number of persons who are photographed persons who have passed a predetermined position; and a passing direction acquiring step for acquiring passing direction information indicating a passing direction in which the person photographed in the image has passed a predetermined position; A count exclusion step of determining whether a person who has passed a predetermined position is a target of count exclusion to be excluded from the count of the number of people in the count step based on the passage direction information acquired in the passage direction acquisition step; , And counting step, if it is determined in the counting exclusion step that it is the target of counting exclusion, counting It excludes the number of the person who is determined to be a target from the count.

  A program according to the present invention is a program readable by an image processing system for counting the number of persons who have passed a predetermined position, the image processing system comprising: acquiring means for acquiring a plurality of images in which a person is photographed; Counting means for counting the number of persons who are persons who are captured in an image and have passed a predetermined position, and passage direction acquisition means for acquiring passage direction information indicating the passage direction in which the person who is captured in the image has passed a predetermined position And function as count exclusion means for determining whether or not a person who has passed a predetermined position is an exclusion target to be excluded from the count of the number of people by the counting means based on the passing direction information acquired by the passing direction acquiring means If the counting means is determined to be the count exclusion target by the count exclusion means, it is determined that the count exclusion target is Is a program for causing the functions to exclude the number of constant is the person from the count.

  According to the present invention, it is possible to provide a mechanism capable of calculating the number of people suitable for the purpose when calculating the number of people who have passed a predetermined position from an image.

FIG. 1 is a system configuration diagram showing an example of a system configuration of an image processing system according to an embodiment of the present invention. It is a figure which shows an example of the hardware constitutions of the information processing apparatus applicable to the server 100 of the image processing system in embodiment of this invention, and client PC101. It is a figure showing an example of the composition of the hardware of network camera 102 in an embodiment of the present invention. It is a functional block diagram which shows an example of a functional structure of the image processing system in embodiment of this invention. It is a figure which shows an example of the image utilized for the people count in embodiment of this invention. It is a figure which shows an example of the image utilized for the passage person count in embodiment of this invention. It is a flowchart which shows an example of the image preservation | save process of the image processing system in embodiment of this invention. It is a flowchart which shows an example of the passing people count process of the image processing system in embodiment of this invention. It is a flowchart which shows an example of the people count process of the image processing system in embodiment of this invention. It is a flowchart which shows an example of the face recognition process of the image processing system in embodiment of this invention. It is a flowchart which shows an example of the browsing process of the image processing system in embodiment of this invention. It is a figure which shows an example of person DB of the image processing system in embodiment of this invention. It is a figure which shows an example of the browsing screen of the people count in embodiment of this invention. It is a figure which shows an example of the browsing screen of passing people count in embodiment of this invention. It is a flowchart which shows an example of the passing people count process of the image processing system which concerns on another embodiment. It is a figure which shows an example of person position information DB. It is a figure which shows an example of border crossing information DB. It is a figure which shows an example of line counter DB. It is a flowchart which shows an example of the count processing of the number of persons shown to the image in the image processing system which concerns on another embodiment. It is a figure which shows an example of the browsing screen of people count.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. The embodiment described below shows an example when the present invention is specifically implemented, and is one of the specific embodiments of the configuration described in the claims.

  FIG. 1 is a system configuration diagram showing an example of a system configuration of an image processing system according to an embodiment of the present invention.

  In an image processing system (information processing system) according to an embodiment of the present invention, a server 100, a client PC 101, and a network camera 102 which is an imaging device are communicably connected via a wireless (or wired) LAN 120. The system configuration of FIG. 1 is an example, and there are various configuration examples according to the application and purpose.

  The server 100 stores and manages image data captured by the network camera 102. The server 100 also has a function of analyzing image data stored and managed by the server 100, counting the number of users included in the image data, and counting the number of people who have passed through a predetermined area.

  The image management system according to the embodiment of the present invention includes a plurality of network cameras 102 (network cameras 102 (A) and (B)), and performs communication by the TCP / IP protocol. A fixed IP address is uniquely assigned, and an external port number assigned to each network group is assigned.

  Therefore, in the server 100, it is possible to identify from which network camera 102 the received image data has been transmitted, and it is possible to identify the received image data and from which network camera 102 it has been transmitted. It is possible to correspond and store and manage.

  The network camera 102 is provided, for example, for each meeting space of the floor of a company building or an entertainment venue (hereinafter also referred to as “predetermined area”). For example, the network camera 102 (A) is a still image of the entire predetermined area or The moving image is taken, and the network camera 102 (B) takes a still image or a moving image to specify the person taken there.

  Examples of the predetermined area include an area 106 indicating the entire area, an area A 103, an area B 104, and the like. A position 105 provided between the area A 103 and the area B 104 is a reference position when counting the number of users (USERs) who have passed the position 105. That is, the present position is a boundary that divides the area A103 and the area B104. The present position may be set to be linear, may be set to be circular, or may be set to be rectangular.

  The client PC 101 is used by the user to browse image data (video of the network camera 102) managed by the server 100. The user can browse image data by logging in to the monitoring system via the client PC 101.

  Next, an example of the hardware configuration of the information processing apparatus applicable to the server 100 and the client PC 101 shown in FIG. 1 will be described using FIG.

  FIG. 2 is a diagram showing an example of a hardware configuration of an information processing apparatus applicable to the server 100 and the client PC 101 of the image processing system according to the embodiment of the present invention.

  In FIG. 2, reference numeral 201 denotes a CPU, which centrally controls devices and controllers connected to the system bus 204. Further, the ROM 202 or the external memory 211 may be a BIOS (Basic Input / Output System) which is a control program of the CPU 201, an operating system program (hereinafter referred to as an OS), and various kinds of later described necessary for realizing functions executed by the PC. Programs and the like are stored.

  A RAM 203 functions as a main memory, a work area, and the like of the CPU 201. The CPU 201 loads programs necessary for execution of processing from the ROM 202 or the external memory 211 to the RAM 203, and implements various operations by executing the loaded programs.

  An input controller 205 controls an input from a pointing device such as a keyboard (KB) 209 or the like. A video controller 206 controls display on a display such as a CRT display (CRT) 210 or the like. Although FIG. 2 describes the CRT 210, the display may be not only a CRT but also another display such as a liquid crystal display.

  A memory controller 207 is an external storage device (hard disk (HD)) for storing a boot program, various applications, font data, user files, editing files, various data, etc., a flexible disk (FD), or a PCMCIA card slot. An access to an external memory 211 such as a CF memory connected via an adapter is controlled.

  A communication I / F controller 208 connects and communicates with an external device via a network, and executes communication control processing in the network. For example, communication using TCP / IP is possible.

  The CPU 201 enables display on the CRT 210 by executing, for example, outline font rasterization processing on a display information area in the RAM 203. Further, the CPU 201 enables user's instruction with a mouse cursor (not shown) on the CRT 210 or the like.

  Various programs to be described later for realizing the present invention are stored in the external memory 211, and are executed by the CPU 201 by being loaded into the RAM 203 as necessary. Furthermore, setting files and the like used at the time of execution of the program are also stored in the external memory 211, and a detailed description of these will be described later. This is the end of the description of FIG.

  Next, an example of the hardware configuration of the network camera 102 shown in FIG. 1 will be described using FIG.

  FIG. 3 is a diagram showing an example of a hardware configuration of the network camera 102 according to the embodiment of the present invention.

  The CPU 301 centrally controls the devices and controllers connected to the system bus 304. Further, the ROM 302 or the external memory 305 is required to realize a function that is executed by the image processing server 108 such as a BIOS (Basic Input / Output System) which is a control program of the CPU 301, an operating system program (OS). Various programs to be described later are stored. The RAM 303 functions as a main memory, a work area, and the like of the CPU 301.

  The CPU 301 loads various programs and the like necessary for execution of processing into the RAM 303 and executes various programs to realize various operations.

  A memory controller (MC) 306 is a CF connected via an adapter to a hard disk (HD) that stores a boot program, various applications, font data, user files, editing files, various data, image data, etc. and a PCMCIA card slot. It controls access to the external memory 305 such as memory and smart media (registered trademark).

  The camera unit 307 is connected to the image processing unit 308, and photoelectrically converts light obtained by transmitting light through a lens directed to a monitoring target by a light receiving cell such as a CCD or CMOS, and then converts the light into an RGB signal. And a complementary color signal to the image processing unit 308.

  The image processing unit 308 performs white balance adjustment, gamma processing, and sharpness processing based on the RGB signal and the color capture signal, and further performs YC signal processing to generate a luminance signal Y and a chroma signal (hereinafter, YC signal). The YC signal is compressed in a predetermined compression format (for example, JPEG format or Motion JPEG format etc.), and this compressed data is temporarily stored in the external memory 305 as image data.

  A communication I / F controller (communication I / FC) 309 is for connecting and communicating with an external device via a network, executes communication control processing in the network, and stores the image stored in the external memory 305. The data is transmitted by the communication I / F controller 309 to an external device. This is the end of the description of FIG.

  FIG. 4 is a functional configuration diagram showing an example of a functional configuration of the image processing system according to the embodiment of the present invention.

  In the image processing system according to the present embodiment, the server 100 has the functions of an image acquisition unit 411, a people count unit 412, a person recognition unit 413, a person exclusion unit 414, and a result screen display control unit 415. Note that the server 100 is not limited to the functional configuration illustrated in FIG. 4 and, for example, a storage unit that stores a person determined to be a count exclusion target, passing direction information indicating a direction in which the person has passed a predetermined position It may have other various functional configurations such as a passing direction acquisition unit to be acquired, and a staying time calculating unit that calculates a time during which a person stays in a predetermined area.

  The image acquisition unit 411 acquires an image captured by the network camera 102 as described in FIG. 7. Images include still images and moving images. In the embodiment, the network camera 102 (A) captures a predetermined area, and the network camera 102 (B) recognizes the identified person (for example, face recognition) and uses it to identify an individual.

  The people counting section 412 counts the number of people in a predetermined area as described with reference to FIG. 9 using an image captured by the network camera 102 (A), and a predetermined number as described with FIG. Count the number of people who passed the position of.

  The person recognition unit 413 uses the image captured by the network camera 102 (B) to authenticate the person shown in the image. An example of the authentication process will be described with reference to FIG.

  Based on the image acquired by the image acquisition unit 411, the person exclusion unit 414 determines whether or not the person shown in the image is a count exclusion target to be excluded from the count of the number of people by the number counting unit 412. The person excluding unit 414 performs processing for specifying a person to be excluded from the number counting by the number counting unit 412, and storing the authenticated person in the person table and the passing person table shown in FIG. For example, the person excluding unit 414 determines whether or not the person who has passed the predetermined position is to be excluded from the count based on passing direction information indicating a passing direction in which the person shown in the image has passed the predetermined position. In addition, the person excluding unit 414 determines whether the person included in the image is to be excluded from the count based on the staying time of the person included in the image in the predetermined area.

  The result screen display control unit 415 performs processing to control to display the image processing result on the terminal of the user according to the request of the user.

  FIG. 5 is a view showing an example of an image used for counting the number of people according to the embodiment of the present invention.

  The image A 501 is an image obtained by capturing a predetermined area at a certain place, and the image B 502 is an image obtained by capturing the same point / same area as the image A at different times. These images are managed as images to be compared.

  In FIG. 5, five persons from Mr. A to Mr. E appear in the image A. For example, in the image B which is an image after 5 minutes, Mr. D and Mr. E disappear even if they are the same five persons. , Mr. F and Mr. G are examples. Here, for example, since Mr. A, Mr. B, and Mr. C are users who are also shown in the image B five minutes ago, they are excluded from the people count. That is, the person excluding unit 414 determines Mr. A, Mr. B, and Mr. C whose staying time in the predetermined area 501 is 5 minutes or more as the count exclusion target. Then, the number counting unit 412 counts the number of people excluding the person determined to be the count exclusion target by the person excluding unit 414.

  In addition, for example, because of the clerk, it is possible to exclude Mr. A from the people count. That is, the person excluding unit 414 may determine that Mr. A is to be excluded from counting based on the fact that the person is a predetermined person. The number counting unit 412 is not limited to the person determined to be a count exclusion target by the person excluding unit 414, and may count the number of people excluding a person set in advance by a manager or the like.

  In the present embodiment, it is configured to be able to display the change situation of the person shown here on the screen shown in FIG.

  FIG. 6 is a view showing an example of an image used for counting the number of passing persons according to the embodiment of the present invention.

  A predetermined area in a certain place is an image taken, and time has elapsed in the order of image A 601 → image B 602 → image C 602.

  Here, the number of people who moved from area A to area B (or vice versa move from area B to area A) based on the predetermined position 604 is counted, and the same person who moves multiple times in the same direction or the default user Can be excluded from the count. Here, the same direction is not limited to exactly the same direction on a straight line from a certain point to a certain point, and means, for example, the same direction as a direction from the first area to the second area. For convenience, with reference to the area A, a case where a person moves to the area B is described as “OUT”, and a case where a person moves from the area B to the area A is counted as “IN”. In this case, the same direction means that both are "OUT" (or both are "IN").

  The image A shows that Mr. C is moving from the area A to the area B (moving the predetermined position 604 from the area A to the area B) (OUT).

  Image B shows that Mr. C moved from Area B to Area A and Mr. D moved from Area B to Area A (IN).

  The image C shows that Mr. C has moved from the area A to the area B again and the A has moved from the area A to the area B (OUT). Here, since Mr. C is the second movement in the same direction, it is excluded from the people count. That is, the person excluding unit 414 determines that Mr. C who passes the predetermined position 604 a plurality of times in the same passage direction is the count exclusion target. Then, the number counting unit 412 counts the number of people excluding the person determined to be the count exclusion target by the person excluding unit 414.

  Also, since Mr. A is predetermined to be excluded in advance, even the first move is excluded. That is, the person excluding unit 414 may determine that Mr. A is to be excluded from counting based on the fact that the person is a predetermined person. The number counting unit 412 is not limited to the person determined to be a count exclusion target by the person excluding unit 414, and may count the number of people excluding a person set in advance by a manager or the like.

  FIG. 7 is a flowchart showing an example of the image storage process of the image processing system according to the embodiment of the present invention.

  The present process is a process of transmitting an image captured by the network camera 102 to the server 100 for storage.

  In step S701, the network camera 102 captures an image of the monitoring area (area 106), and transmits the image captured in step S702 to the server.

  In step S703, the server 100 receives an image from the network camera 102. In step S704, the server 100 stores the image received as a recording file in the external memory 211 of the server or the like, and ends the processing.

  The image processing system counts the number of users or the number of passing users shown in the image using the image saved here.

  FIG. 8 is a flowchart showing an example of passing people counting processing of the image processing system according to the embodiment of the present invention.

  This process is a process of counting how many users have passed through a predetermined position (for example, 604) set in a predetermined area (for example, 601), and an image of a predetermined time from an image stored in the server Process as target.

  In step S801, the process is repeatedly performed for a predetermined time designated by the user or the administrator. In this embodiment, it will be described that five minutes from 9:00 to 9:05 are designated. Also, in actuality, in order to convert 5 minutes into a moving image, it is composed of a large number of images, but in the present embodiment, explanation will be made using three images for convenience.

  It is assumed that the image 601 is captured at 9:00, the image 602 is captured at 9:03, and the image 603 is captured at 9:05.

  In step S802, line passage detection area information is read. Specifically, it is determined whether there is a person who has passed the predetermined position 604.

  If the person can be identified (recognized) in step S 803, the process advances to step S 804. If the person can not be identified (recognized), the process advances to step S 811 to perform loop determination (whether predetermined time has elapsed).

  In step S804, passage direction information indicating a direction in which a person who has been determined to have passed the predetermined position in step S802 by image analysis processing or the like is acquired (passing direction acquisition means). The passing direction information is information indicating either the first direction from the area A to the area B or the second direction from the area B to the area A, and here, the movement from the area A to the area B The “first direction” is “OUT”, and the movement from the region B to the region A (second direction) is “IN” (the reverse is also possible).

  In step S805, processing for specifying the person recognized in step S803 is performed. This process is described with reference to FIG. 10, but is a process of specifying a recognized person (person specifying means). By this process, unnecessary persons can be excluded from the people count among the identified persons.

  In step S806, it is determined whether the person recognized in step S803 is to be excluded from counting. If it is determined in step S806 that the target person is the count exclusion target, the process proceeds to step S808, the movement of the person is stored as the count exclusion target (storage means) and is not reflected in the people count, and the process proceeds to step S809. move on. If it is determined in step S806 that the target person is not the count exclusion target, the process proceeds to step S807, the movement count of IN / OUT is incremented, and the process proceeds to step S809.

  In step S809, confirmation is made as to whether all the processes of the person recognized in step S803 have been completed. If not completed, the process returns to step S804 and the process for the next person is performed, and the process for all persons is completed. The process proceeds to step S810.

  In step S810, the contents processed in this flow are stored in the result table, and the process ends. Note that this process may be saved collectively in this step, or may be saved each time in each step of the flowchart.

  Next, a result table (person table) stored in this flowchart will be described using FIG.

  FIG. 12 is a diagram showing an example of the person DB of the image processing system according to the embodiment of the present invention. The person DB 1200 is a result table in which the result of the people counting process described in FIG. 9 is stored. In the person DB 1200, user names of users recognized in the images A and B and types of the users are stored. Details will be described later.

  The passing person DB 1210 is an example of a passing person DB, which is a result table stored in the line passage count processing of FIG. 8.

  The passing person DB 1210 stores an image 1211, a time 1212 at which the image was captured, a passing direction 1213, a user 1214, and a counter 1215 in association with each other.

  An image 1211 is an image name, for example, a file name of the image. The images A to C respectively correspond to the images A601 to C603 in FIG. 6, and are photographed at 9:00, 9:03, and 9: 5, respectively.

  As the passing direction 1213, the direction detected in step S804 is stored, and the user 1214 stores the user specified in step S805.

  The counter 1215 is an IN / OUT counter in step S807, and is a counter of the number of IN users and OUT users. For example, it can be seen that OUT was counted by two and IN was counted by one.

  In addition, Mr. C of image C is excluded. This is due to the setting that “movement of the same user in the same direction within a predetermined time is excluded from counting”. That is, the person excluding unit 414 determines that the same user who moves in the same direction within the predetermined time is the count exclusion target, and the determination result is stored in the result table.

  In addition, Mr. A of image C is excluded. This is due to the setting that "Mr. A is default (excluded)" as shown in FIG. That is, the person excluding unit 414 determines that the predetermined user is the count exclusion target person, and the determination result is stored in the result table. The setting can be set by an administrator in advance as well as this setting.

  FIG. 9 is a flowchart showing an example of the process of counting the number of persons of the image processing system according to the embodiment of the present invention.

  The present process is a process of counting how many users appear in a predetermined area (for example, 501), and targets an image stored in the server.

  For example, although five images are shown in both the image A 501 and the image B 502, two images are compared, the same user is excluded, a predetermined user is excluded, or only the number of new users is displayed. Processing can be performed. That is, the present invention is not limited to the preset exclusion target person, and it is determined whether or not the person is the count exclusion target based on the image, and processing for excluding the person determined to be the count exclusion target from the people count. It can be carried out.

  Further, since the present process compares images, the number of people in the set number is counted, and in the present embodiment, two images A and B have a predetermined number. .

  In step S901, area information is read. The area information is, for example, the area 106 in FIG. 1 and corresponds to the image of the area preset and photographed by the network camera 102.

  In step S902, it is determined whether a person has been identified (recognized) in the area. If the person has been identified, the process advances to step S903 to perform person identification processing. The person specifying process will be described with reference to FIG. 10. However, the person specifying process determines whether the recognized person is an exclusion target.

  In step S904, it is determined whether the person recognized in step S902 is an exclusion target. If it is determined that the person is an exclusion target, the process proceeds to step S906, and it is determined that the person is not an exclusion target. The process proceeds to step S905.

  In step S906, the person determined to be an exclusion target is not reflected in the number of people, and the process proceeds to step S907. In step S905, the number of persons recognized in step S902 is counted, and the process proceeds to step S907.

  In step S 907, it is determined whether the processing for all the images (two in this case) is completed. If the processing is not completed, the process returns to step S 903. If the processing is completed, the process proceeds to step S 908. Save the contents of the process in the result table and end the process. Note that this process may be saved collectively in this step, or may be saved each time in each step of the flowchart.

  The result table stored in the flowchart will be described using the person DB 1200 in FIG. The image A is an image captured at 9:00, and the image B is an image captured at 9: 5.

  The person DB 1200 manages, for each image, the number of recognized users and whether the user is an exclusion target.

  In the person DB 1200 corresponding to the image A, a user type 1201 and a user name are stored. Information of five persons of users A to E recognized based on the image 501 of FIG. 5 is stored in the person DB 1200 as the user name 1202. In addition, the user type 1201 of the user A who is excluded by default is set as “default”. .

  In the person DB 1200 corresponding to the image B, information of five persons of users A to C, F, and G is stored as the user name 1204. The user types 1203 of the users F and G who are users (new) not present in the image A are blank.

  In addition to the user type 1204 of the user A being "default", the user types 1204 of the users A to C specified also in the image A are stored as (specified and A) as "specified". There is. That is, the person excluding unit 414 determines that the same user located on the same floor is the count exclusion target even after a predetermined time has elapsed, and stores the determination result in the result table. Here, it is assumed that a specified user or a default user is treated as an exclusion target.

  FIG. 10 is a flowchart showing an example of face recognition processing of the image processing system according to the embodiment of the present invention.

  This face recognition process corresponds to the person specifying process of S805 of FIG. 8 and step S903 of FIG. In the present embodiment, person identification processing by face recognition will be described. However, if a person can be identified, the present invention is not limited to face recognition processing, and any technique may be used.

  In step S1001, the person image recognized in the image is received, and in step S1002, the feature points of the person are cut out to identify the individual. The process of extracting the feature points of the person and performing individual identification uses the already proposed technology.

  In step S1003, it is checked whether or not the identified person is registered in the result table (in FIG. 8, the passing person DB 1210, in FIG. 9, the person DB 1200), and in the case of being registered, in step S1006. If it is not registered, the process proceeds to step S1004.

  In step S1006, the persons registered in the result table are returned as excluded persons (exclusion targets). In the case of the person DB 1200, “registered” is determined based on whether or not the user types 1201 and 1203 are registered as exclusion targets. Specifically, in the case of image A, Mr. A is excluded because the user type is default, and in the case of image B, Mr. A of default and Mr. A to C as identified persons are excluded persons (exclusion target) The reply is sent and the process ends.

  Further, in the case of the passing person DB 1210, Mr. A of the default and Mr. C (OUT) of the image C which is the second movement (movement multiple times) in the same direction are returned as excluded persons (exclusion targets) and processed Ends.

  In step S1004, the person determined as not registered in step S1003 is registered (as exclusion) in the result table. For example, in person DB 1200, persons A to C who have not been registered based on being specified in person DB 1200 corresponding to image A have already been specified in image A in person DB 1200 corresponding to image B. Is registered.

  In addition, in the passing person DB 1210, Mr. C (OUT) of the image C, which is a case where the same user is moving in the same direction and is not registered, and Mr. A of the image C (OUT, when the default user is・ Default) is registered as an exclusion target. Subsequently, in step S1005, the person registered in step S1004 is returned as a non-exclusion person (non-exclusion target), and the process ends.

  FIG. 11 is a flowchart showing an example of the browsing process of the image processing system according to the embodiment of the present invention.

  The present process is a process of displaying and controlling the result of the image processing on the terminal of the user according to an instruction from the user.

  In step S1101, a camera to be displayed is selected. For example, the serial number or the name of the network camera 102 (A) is selected, and an image photographed by the selected camera is requested in step S1102. This image may be a still image format, a moving image format, or a LIVE moving image.

  In step S1103, it is determined whether the requested image is the people count (FIG. 5) or the line passing people count (FIG. 6). If it is the people count, the process proceeds to step S1104. If it is LINE passage, the process proceeds to step S1105. move on.

  In step S1104, processing is performed to display a browsing screen of the number of people count shown in FIG. 13 as the number of people information. In step S1105, processing is performed to display the browsing screen of the passing people count shown in FIG. The details of the browsing screen will be described later with reference to FIGS. 13 and 14.

  In step S1106, processing for combining the items to be displayed on the browsing screen is performed, and in step S1107, display control of the screen is performed to be displayed on the screen of the client, and the processing ends.

  FIG. 13 is a diagram showing an example of a browsing screen of people count according to the embodiment of the present invention.

  Two examples of the people count browsing screen 1301 and the people count browsing screen 1310 will be described.

  In the people count viewing screen 1301, the current image 1302, the recognized number of people (5) 1303, the default exclusion target (1 person) 1304, the personal identification already excluded exclusion target (3 persons) 1305, and the new screen The recognized person and number of people (two people) 1306 are displayed.

  The number-of-people count browsing screen 1310 is another browsing screen example of 1301 and can be displayed including the display contents of 1301.

  The count number excluding the exclusion target person, the predetermined exclusion target number 1311 and the acquired image are displayed.

  In addition, the visibility may be enhanced by displaying the counted person in a frame such as a thick frame, and it is possible to distinguish Mr. A, who is the default excluded person, from other users by different colors and lines. It may be displayed on

  In addition, the user name that can be identified individually in the person identification process is displayed by combining the user name (for example, Mr. A or Mr. B) and the display is different such that nothing is displayed for the user who can not identify the individual. Is also valid.

  FIG. 14 is a view showing an example of a browsing screen of passing people count according to the embodiment of the present invention.

  Two examples of the passing people count viewing screen 1401 and the passing people count viewing screen 1410 will be described.

  In the passing people count viewing screen 1401, the number and direction 1402 of passing the predetermined line (position), the default exclusion target (one person) 1403, and the excluded person and the number 1404 of passing twice are displayed.

  The passing people count viewing screen 1410 is another viewing screen example of 1401 and can be displayed including the display contents of 1401.

  The number of persons passing / direction / number of exclusions 1411 and the acquired image are displayed. In the example, IN (one person), OUT (two person), and the exclusion number (two persons) are included, but the exclusion number includes both of 1403 and 1404 exclusion targets.

  In the image, the visibility may be enhanced by displaying the people counted by line passage by surrounding them with a frame such as a thick frame, and Mr. A, who is the default excluded person, with different colors and lines. It may be displayed distinguishably from other users. In addition, the user 1412 that has not passed through the line can be displayed distinguishably from the person who passed (without showing a dotted line for convenience but may not have to display anything), without displaying cooperatively with a frame or the like. It is.

  In addition, the user name that can be identified individually in the person identification process is displayed by combining the user name (for example, Mr. A or Mr. B) and the display is different such that nothing is displayed for the user who can not identify the individual. Is also valid.

  Next, an image processing system according to another embodiment applicable to the case of performing passing people count processing will be described. In the other embodiment, the person excluding unit 414 repeatedly (passes over) a person who goes over the boundary line, who is crawling on the boundary line, that is, a predetermined position within a predetermined time (for example, about 5 minutes). The point which determines whether it is a count exclusion object based on whether it is a person differs from the said embodiment. Hereinafter, this determination is also referred to as "smooth exclusion determination".

  Hereinafter, the other embodiment will be described in detail with reference to FIG. FIG. 15 is a flowchart showing an example of passing people counting processing of the image processing system according to another embodiment.

  The present process is a process for counting the number of passers, which counts how many users have passed through a predetermined boundary line (for example, the position 604) set in a predetermined area (for example, the area captured in the image 601). It is a process which excludes the person who passes repeatedly along the boundary line from people count. This process is performed by the server 100 of the image processing system.

  The present process starts, for example, when a user inputs a start instruction to start the present process. Further, for example, when it is determined that all persons have been analyzed in step S1504 to be described later, when an end instruction from the user is input, or when a preset processing time is completed, etc. finish.

  First, in step S 1501, boundary line information and a bracing interval time are acquired. The boundary line information and the bracing time interval are acquired from, for example, setting information set in advance by a user or the like.

  The boundary line information is position information of the boundary line, and is indicated by pixel coordinates based on the upper left end of the image 601, for example. The interval time during which the same person passes the boundary line a plurality of times is not simply passing through the boundary line to move from the area A to the area B (or from the area B to the area A). It is a time that is considered to be crawling on the boundary line, and is set to, for example, 5 minutes.

  Subsequently, in step S1502, the image acquisition unit 411 acquires an image captured by the network camera 102. The image acquisition unit 411 acquires, for example, an image captured within a predetermined time.

  Subsequently, in step S1503, the person recognition unit 413 recognizes all the persons and their positions in the image acquired in step S1503, and creates a list of all the persons and their positions on the memory.

  Subsequently, in step S1504, it is determined whether there is a person who is not analyzed on the list created in step S1503. Here, analysis means performing the process of step S1505 and subsequent steps described later.

  If it is determined that there is no person who has not been analyzed (step S1504; NO), that is, if all the people have been analyzed, the process ends. In this case, the process may return to the process of step S1503 without ending the process, the image may be acquired again, and the processes after step S1504 may be repeated.

  If it is determined that there is a person who is not analyzed (step S1504; YES), the process proceeds to step S1505. That is, the processes in step S1505 and subsequent steps are repeated until analysis is completed for all persons.

  Subsequently, in step S1505, among the unprocessed persons not analyzed on the list created in step S1503, the personal information to be analyzed next is acquired.

  Subsequently, in step S1506, the person recognition unit 413 recognizes the same person as the person indicated by the person information to be analyzed next acquired in step S1505.

  Subsequently, in step S1507, the person recognition unit 413 caches the position information of the person who is recognized as the same person in step S1506. Specifically, it is stored as a person position information DB 1600 as shown in FIG. FIG. 16 is a diagram showing an example of the person position information DB 1600.

  As shown in FIG. 16, in the person position information DB 1600, a time stamp 1601, a person ID 1602, a camera ID 1603 and position information 1604 are stored in association with one another.

  The time stamp 1601 is a character string indicating the date and time when an image of a person was recognized by the network camera. In the example of FIG. 16, the date and time of the time stamp 1601 are stored so as to be arranged in order from the top in chronological order. For example, “2012.07.27 12: 00: 00: 00” is stored as the time stamp 1601 next to “2012.07.27 12: 00: 01: 00” as the time stamp 1601. That is, the date and time when the time stamp 1601 is "2012.07.27 12: 00: 00: 00" and the date and time when the time stamp 1601 is "2012.07.27 12: 00: 01: 00" are mutually time-series It is in context. Hereinafter, among the dates and times in such a sequential relationship, the time before the time stamp 1601 is "2012.07.27 12: 00: 00: 00" may be simply referred to as "the previous time", and the time stamp 1601 may be "2016.07. 27 The time after 12: 00: 01: 00 is also simply referred to as "aftertime".

  Although illustration is omitted in the example of FIG. 16, actually, data associated with the time stamp 1601 of a predetermined time including the date and time before the date and time of the time stamp 1601 illustrated is stored. There is.

  The person ID 1602 is identification information indicating the person recognized in step S1506. The camera ID 1603 is identification information indicating the network camera 102 that has captured the person recognized in step S1506. Position information 1604 is position information of the person recognized in step S1506, and is indicated by pixel coordinates based on the upper left end of the image 601, for example. The position information 1604a is position information indicated by an X coordinate, and the position information 1604b is position information indicated by a Y coordinate.

  Referring again to FIG. 15, in the subsequent step S1508, the movement position and movement direction within a predetermined time such as one hour are calculated based on the person position information DB 1600 for the person recognized as the same person in step S1506.

  The movement position is a position at which the same person moves within a predetermined time. The movement position is calculated, for example, as each position indicated by position information 1604 associated with the same person ID 1602 and a time stamp 1601 within a predetermined time.

  The movement direction is the direction in which the same person has moved within a predetermined time. The movement direction is calculated, for example, as a vector indicating the direction from the position at the previous time to the position at the later time based on the calculated positions.

  Subsequently, in step S1509, it is determined based on the boundary line information acquired in step S1501 and the movement position and movement direction calculated in step S1508 whether or not the same person has passed the boundary line.

  If it is determined that the same person has not passed the boundary line (step S1509; NO), the process returns to step S1504, and it is determined whether there is a person who has not been analyzed. If it is determined that the same person has passed the boundary line (step S1509; YES), the process proceeds to step S1510.

  In step S1510, passage information of the boundary line is cached for the person determined to have passed through the boundary line in step S1509. Specifically, the passage information of the boundary line is stored as the boundary-boundary information DB 1700 as shown in FIG. FIG. 17 is a diagram showing an example of the boundary crossing information DB 1700.

  As shown in FIG. 17, in the boundary crossing information DB 1700, a time stamp 1701, a person ID 1702, a camera ID 1703, and a boundary crossing direction 1704 are stored in association with one another.

  The timestamp 1701 is a character string indicating the time when the same person passes the boundary line. The person ID 1702 is identification information indicating a person determined to have passed the boundary line in step S1509. The camera ID 1703 is identification information indicating the network camera 102 that has photographed the person determined to have passed the boundary line in step S1509.

  The over-boundary direction 1704 is information indicating a direction beyond the border line of the person determined to have passed through the border line in step S1509, and is indicated by "IN" or "OUT" described above. The over-boundary direction 1704 is calculated based on, for example, the movement position and movement direction calculated in step S1508 and the boundary line information acquired in step S1501 (passing direction information acquisition unit), and is stored.

  Subsequently, in step S1511, the boundary crossing information DB 1700 stored in step S1510 is referenced, and a plurality of pieces of information in which the same person passes the boundary line within a predetermined time (for example, one hour) are searched.

  Subsequently, in step S1512, based on the information searched in step S1511, it is determined whether the border line is passed over. For example, movement in the opposite direction (movement from “IN” to “OUT” or “OUT” to “IN”) is one time within the crawling interval time (for example, 5 minutes) acquired in step S1501. If there is more than one, it is determined that the boundary line is passed around.

  If it is determined in step S1512 that the boundary line is being passed back and forth (step S1512; YES), the process proceeds to step S1513. In step S1513, the person excluding unit 414 determines that the person who has passed the boundary line is the count exclusion target, and the number counting unit 412 excludes from the count the number of persons who are determined to be the count exclusion target. After step S1513, the process returns to step S1504 to determine again whether there is a person who has not been analyzed.

  In the present specification, excluding from the count includes not only incrementing the number of people but also decrementing the count once incremented.

  If it is determined in step S1512 that the boundary line has not passed over the border (step S1512; NO), the process proceeds to step S1514 to perform the same process as normal people count processing. Specifically, first, in step S1514, based on the information retrieved in step S1511, it is determined whether the same person has moved in the same direction a plurality of times.

  If it is determined in step S1514 that the user has moved multiple times in the same direction (step S1514; YES), the process proceeds to step S1515, and the person excluding unit 414 determines that the person who has passed the boundary line is the count exclusion target. The counting unit 412 excludes from the count the number of persons determined to be excluded from counting. After step S1514, the process returns to step S1504, and it is determined again whether or not there is a person who has not been analyzed.

  If it is determined in step S1514 that the user has not moved a plurality of times in the same direction (step S1514; NO), the process advances to step S1516 to increment the count of the number of people who have passed the boundary line for each passing direction of IN / OUT. After step S1516, the process returns to step S1504, and it is determined again whether there is a person who has not been analyzed.

  The result of the people count incremented in step S1516 is stored, for example, as a line counter DB 1800 as shown in FIG. FIG. 18 is a diagram showing an example of the line counter DB 1800. As shown in FIG.

  As shown in FIG. 18, in the line counter DB 1800, a time stamp 1801, a camera ID 1802, and a count number 1803 are stored in association with one another.

  The timestamp 1801 is a character string indicating the latest date and time when the people count is incremented. The camera ID 1802 is identification information indicating the network camera 102 that has photographed a person whose count is incremented. The count number 1803 is the camera ID and the number of people incremented for each passing direction, and is the total number of people added from a certain starting point. The count number 1803a is the number of people who have passed in the “IN” direction, and the count number 1803b is the number of people who have passed in the “OUT” direction.

  As shown in FIG. 18, in step S1506, the camera ID and the number of people counted for each passing direction are stored.

  As described above, according to the present embodiment, after the same person moves in the first direction (for example, “IN”) based on the passing direction in which the person passes the boundary line, the second direction is detected within the predetermined tailing interval time. When moving to (for example, “OUT”), the same person is excluded from the passage count. Therefore, the number of people who pass the boundary line to move from the region A to the region B (or from the region B to the region A), but merely crawling over the boundary line is counted. Noise can be removed.

  Next, an image processing system according to another embodiment applicable to the case of performing the process of counting the number of people captured in an image will be described. The second embodiment is different from the first embodiment in that the person excluding unit 414 determines at least one of the long staying person and the short staying person in the predetermined area as the count exclusion target.

  Hereinafter, the other embodiment will be described in detail with reference to FIG. FIG. 19 is a flowchart illustrating an example of a process of counting the number of persons shown in an image in an image processing system according to another embodiment.

  The present process counts the number of people staying for a long time and / or for a short time stay in a predetermined area (for example, a partial area in the area 601) in the people counting process of counting the number of people included in the image. It is processing to exclude from. This process is performed by the server 100 of the image processing system.

  The present process starts, for example, when a user inputs a start instruction to start the present process. In addition, for example, when it is determined in step S1904 described later that analysis has been performed for all persons, when an end instruction from the user is input, or when a preset processing time is completed, etc. finish.

  First, in step S1901, position information of a stay area and a stay determination time are acquired. The position information of the predetermined area and the stay determination time are acquired from, for example, setting information set in advance by the user or the like.

  A stay area, for example, a part of a predetermined area in the area 601 is an area surrounded to have a predetermined shape such as a rectangle or a circle. The position information of the staying area is indicated, for example, by pixel coordinates with reference to the upper left end of the image that shows the area 601. The stay determination time is a time for determining whether the time during which the same person stays in the stay area is a long time or a short time. The stay determination time is, for example, a long stay determination time (for example, one hour) for determining whether or not it is a long time, and a short stay determination time for which it is determined whether or not it is a short time (for example, 10 minutes) and.

  The subsequent processes of steps S1902 to S1907 are the same as the processes of steps S1502 to S1507 in FIG. 15 described above, and thus the description thereof will be omitted.

  In step S1908 following step S1907, is the same person recognized in step S1906 in the stay area based on the position information of the stay area acquired in step S1901 and the position information of the person cached in step S1907? It is determined whether or not.

  If it is determined in step S1908 that the same person is not in the stay area (step S1908; NO), the process returns to step S1904, and it is determined whether there is a person who has not been analyzed. If it is determined in step S1908 that the same person is in the stay area (step S1908; YES), the process proceeds to step S1909.

  In step S1909, the stay time of the same person determined to be in the stay area in step S1908 is calculated. Specifically, based on the person position information DB 1600 stored in step S1907, the latest time slot linked to the same person determined to be in the stay area is searched, and the oldest time in the time slot is searched. By calculating the difference with the latest time, the stay time of the same person is calculated.

  Subsequently, in step S1910, it is determined whether the stay time calculated in step S1909 is equal to or longer than the long stay determination time acquired in step S1901. That is, it is determined whether or not the recognized same person is a long-time stayer staying in the stay area for a predetermined time (for example, one hour) or more.

  If it is determined in step S1910 that the stay time is equal to or longer than the long stay determination time (step S1910; YES), the process proceeds to step S1911. In step S1911, the person excluding unit 414 determines that the person determined to be a long-time resident is to be excluded from counting, and the number counting unit 412 excludes the number of persons determined to be excluded from counting from the count. . After step S1911, the process returns to step S1904, and it is determined again whether there is a person who has not been analyzed.

  The person whose count is excluded in step S1911 is stored as the count exclusion target due to long-term stay at the timing when the count is excluded. In addition, the number of people excluded from counting in step S1911 is incremented as the number of people excluded from counting due to long-term stay at timing when the count is excluded.

  If it is determined in step S 1910 that the stay time is not longer than the long stay determination time (step S 1910; NO), the process proceeds to step S 1912. In step S1912, it is determined whether the stay time calculated in step S1909 is equal to or greater than the short stay determination time acquired in step S1901. That is, it is determined whether the recognized same person is a short time staying person who has stayed for less than a predetermined time (for example, 10 minutes) in the stay area.

  If it is determined in step S1912 that the stay time is less than the short stay determination time (step S1912; YES), the process proceeds to step S1913. In step S1913, the person excluding unit 414 determines that the person determined to be a short-time resident is to be excluded from counting, and the number counting unit 412 excludes from the count the number of persons determined to be excluded from counting. . After step S1913, the process returns to step S1904, and it is determined again whether there is a person who has not been analyzed.

  The person whose count is excluded in step S1913 is stored as a count exclusion target due to short-term stay at timing when the count is excluded. In addition, the number of people excluded from counting in step S1913 is incremented as the number of people excluded from counting due to short-term stay at timing when the count is excluded.

  If it is determined in step S1912 that the stay time is not less than the short stay determination time (step S1912; NO), the process proceeds to step S1914 and the people counter is incremented. That is, it is possible to count only persons who are staying for a short time determination time or more and less than a long time determination time. Hereinafter, a time which is equal to or more than a short time judgment time and less than a long time judgment time may be referred to as an "appropriate time", and a person whose stay time is an appropriate time may be referred to as an "appropriate time stay person". After step S1914, the process returns to step S1904, and it is determined again whether there is a person who has not been analyzed.

  In the present embodiment, the result screen display control unit 415 displays, for example, a screen shown in FIG. 20 as a browsing screen for browsing the result of the people count.

  FIG. 20 is a diagram showing an example of a browsing screen of the number of people. As shown in FIG. 20, on the browsing screen, the number of people 2001 who has counted excluding the count exclusion target and the number of people 2002 who have been count-excluded as the count exclusion target are displayed.

  In addition, among the number of people 2002 who are excluded from being counted out, the number of people 2003 who are excluded as long stayers and the number of people 2004 who are excluded from counting as short stayers are displayed distinguishably. .

  Further, among the persons staying in the stay area 2005 indicated by the one-dot chain line, the long stayers, the short stayers, and the appropriate stayers are displayed so as to be distinguishable.

  For example, a long-time stayer is displayed surrounded by a solid rectangular frame 2006, a short-time stayer is displayed surrounded by a dashed rectangular frame 2007, and a proper stayer is displayed without being surrounded by anything. In addition, the stay time in the stay area 2005 of each person may be displayed.

  As described above, according to the present embodiment, since long-term stayers and short-time stayers in the stay area are excluded from the count, only appropriate-time stayers who are neither long-time stayers nor short-term stayers in the stay area are counted. can do. The appropriate time can be set to a desired time of the user by appropriately changing and setting the long stay determination time and the short time determination time. Therefore, the person who has stayed for the appropriate time which a user desires can be counted.

  Moreover, according to the present embodiment, the long-time stayer, the short-time stayer, the appropriate stayer, and the number of persons are displayed in a distinguishable manner. Therefore, it is possible to easily grasp how much the person staying in the stay area continues to stay in the stay area.

  In the present embodiment, although an example has been described in which long-time stayers and short-time stayers in the stay area are excluded from the counting, the present invention is not limited thereto, either long-time stayers or short-time stayers in the stay area One may be excluded from the count. For example, in the case where only long-time residents are excluded from the count, the short-time determination time may be set to zero. In addition, in the case where only short-term residents are excluded from the counting, the long time determination time may be set to a very large value.

  Although the embodiments have been described above, the present invention can also be embodied as, for example, a system, an apparatus, a method, a program, a storage medium, etc. Specifically, the present invention is applied to a system including a plurality of devices. It may be applied to an apparatus consisting of one device.

  Note that the present invention includes one that directly or remotely supplies a program of software that implements the functions of the above-described embodiments to a system or an apparatus. The present invention is also included in the present invention if the computer of the system or apparatus reads out and executes the supplied program code.

  Therefore, the program code itself installed in the computer to realize the functional processing of the present invention by the computer also implements the present invention. That is, the present invention also includes a computer program itself for realizing the functional processing of the present invention.

  In that case, as long as it has the function of a program, it may be in the form of an object code, a program executed by an interpreter, script data supplied to an OS, or the like.

  Examples of recording media for supplying the program include a flexible disk, a hard disk, an optical disk, a magneto-optical disk, an MO, a CD-ROM, a CD-R, and a CD-RW. There are also magnetic tapes, non-volatile memory cards, ROMs, DVDs (DVD-ROMs, DVD-Rs) and the like.

  In addition, as a program supply method, a browser on a client computer is used to connect to an Internet home page. Then, the program can be supplied by downloading the computer program of the present invention itself or a compressed file including an automatic installation function from the home page to a recording medium such as a hard disk.

  The present invention can also be realized by dividing the program code constituting the program of the present invention into a plurality of files and downloading each file from different home pages. That is, the present invention also includes a WWW server which allows a plurality of users to download program files for realizing the functional processing of the present invention by a computer.

  In addition, the program of the present invention is encrypted, stored in a storage medium such as a CD-ROM, and distributed to users, and the user who has cleared predetermined conditions downloads key information that decrypts encryption from the homepage via the Internet. Let Then, it is possible to execute the program encrypted by using the downloaded key information and install it on a computer.

  Also, the functions of the above-described embodiments are realized by the computer executing the read program. In addition, based on the instructions of the program, an OS or the like running on the computer performs part or all of the actual processing, and the functions of the above-described embodiment can be realized by the processing.

  Furthermore, the program read from the recording medium is written to a memory provided in a function expansion board inserted in the computer or a function expansion unit connected to the computer. Thereafter, based on the instruction of the program, a CPU or the like provided in the function expansion board or the function expansion unit performs part or all of the actual processing, and the function of the above-described embodiment is also realized by the processing.

  The embodiments described above merely show examples of implementation in practicing the present invention, and the technical scope of the present invention should not be interpreted in a limited manner by these. That is, the present invention can be implemented in various forms without departing from the technical concept or the main features thereof.

100 server 101 client PC
102 Network Camera

The image processing system according to the present invention is an image processing system capable of counting the number of persons who have passed a predetermined position, and an acquisition unit for acquiring a plurality of images in which a person is photographed, and an image processing system A counting means for counting the number of persons who are persons who have passed a predetermined position, a passing direction acquiring means for obtaining passing direction information indicating a passing direction in which the person shown in the image has passed a predetermined position , And a person specifying means for specifying a person who satisfies a predetermined condition based on the passing direction information acquired by the passing direction acquiring means among the persons who have passed the position .

A control method of an image processing system according to the present invention is a control method of an image processing system that counts the number of persons who have passed a predetermined position, and an acquisition step of acquiring a plurality of images in which a person is photographed; A counting step for counting the number of persons who are photographed persons who have passed a predetermined position; and a passing direction acquiring step for acquiring passing direction information indicating a passing direction in which the person photographed in the image has passed a predetermined position; And a person specifying step of specifying a person who satisfies a predetermined condition based on the passing direction information acquired in the passing direction acquiring step among the persons who have passed through the predetermined position .

A program according to the present invention is a program readable by an image processing system for counting the number of persons who have passed a predetermined position, the image processing system comprising: acquiring means for acquiring a plurality of images in which a person is photographed; Counting means for counting the number of persons who are persons who are captured in an image and have passed a predetermined position, and passage direction acquisition means for acquiring passage direction information indicating the passage direction in which the person who is captured in the image has passed a predetermined position And a program for functioning as a person specifying means for specifying a person who satisfies a predetermined condition based on the passing direction information acquired by the passing direction acquiring means among the persons who have passed through the predetermined position .

Claims (11)

An image processing system capable of counting the number of persons who have passed a predetermined position
Acquisition means for acquiring a plurality of images in which a person is photographed;
Counting means for counting the number of persons appearing in the image and having passed the predetermined position;
Passing direction acquisition means for acquiring passing direction information indicating a passing direction in which a person captured in the image has passed the predetermined position;
Counting exclusion means for determining whether or not a person who has passed the predetermined position is a counting exclusion target to be excluded from the counting of the number of people by the counting means based on the passing direction information obtained by the passing direction obtaining means And
The image processing system, wherein the counting means excludes, from the count, the number of persons determined to be the count exclusion target, when the count exclusion means determines that the count exclusion target is the target.   The image processing system according to claim 1, further comprising storage means for storing a person determined to be the count exclusion target by the count exclusion means. The passing direction is one of a first direction from a first area dividing the predetermined position toward a second area and a second direction from the second area toward the first area.
When the same person shown in the image passes the predetermined position a plurality of times in the same passing direction as one of the first direction and the second direction, the count excluding means may be the same person. The image processing system according to claim 1, wherein the image processing system is determined to be the count exclusion target. The passing direction is one of a first direction from a first area dividing the predetermined position toward a second area and a second direction from the second area toward the first area.
When the same person captured in the image passes through the predetermined position in the first direction, the count exclusion means passes the predetermined position in the second direction within the predetermined time. The image processing system according to any one of claims 1 to 3, wherein the same person is determined as the count exclusion target.   The image processing system according to any one of claims 1 to 4, wherein the counting means counts the number of people for each passing direction indicated by the passing direction information acquired by the passing direction acquiring means.   The count exclusion means excludes the person who passed the predetermined position based on a combination of the person who has passed the predetermined position and the passing direction indicated by the passing direction information acquired by the passage direction acquiring means. The image processing system according to any one of claims 1 to 5, wherein it is determined whether or not it is a target. A display control unit configured to display and control the number of persons who have passed the predetermined position;
7. The display control means according to any one of claims 1 to 6, wherein the display control means performs display control of the number of people counted by the counting means excluding the count exclusion target person and the number of the count exclusion target person. Image processing system described in. 8. The image processing system according to claim 7, wherein the display control means displays the person whose number has been counted excluding the count exclusion target by the counting means so as to distinguishably display the count exclusion target person. It further comprises an imaging device for capturing the image;
The image processing system according to any one of claims 1 to 8, wherein the acquisition unit acquires an image captured by the imaging device. A control method of an image processing system for counting the number of persons who have passed a predetermined position,
An acquisition step of acquiring a plurality of images in which a person is photographed;
A counting step for counting the number of persons appearing in the image and having passed the predetermined position;
A passing direction obtaining step of obtaining passing direction information indicating a passing direction in which a person captured in the image has passed the predetermined position;
A count exclusion step of determining whether a person who has passed the predetermined position is a count exclusion target to be excluded from the count of the number of people in the count step based on the passage direction information acquired in the passage direction acquisition step And, and
The control method of the image processing system, wherein the counting step excludes, from the counting, the number of persons determined to be the count exclusion target when it is determined that the count exclusion target is the target in the count exclusion step. A program readable by an image processing system for counting the number of persons who have passed a predetermined position, comprising:
Image processing system
Acquisition means for acquiring a plurality of images in which a person is photographed;
Counting means for counting the number of persons appearing in the image and having passed the predetermined position;
Passing direction acquisition means for acquiring passing direction information indicating a passing direction in which a person captured in the image has passed the predetermined position;
Counting exclusion means for determining whether or not a person who has passed the predetermined position is a counting exclusion target to be excluded from the counting of the number of people by the counting means based on the passing direction information obtained by the passing direction obtaining means To act as
A program for causing the counting means to exclude from the count the number of persons determined to be the count exclusion target when the count exclusion means determines that the count exclusion target is the count exclusion target.

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