CN108848300A - Method and apparatus for output information - Google Patents
Method and apparatus for output information Download PDFInfo
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- CN108848300A CN108848300A CN201810429487.3A CN201810429487A CN108848300A CN 108848300 A CN108848300 A CN 108848300A CN 201810429487 A CN201810429487 A CN 201810429487A CN 108848300 A CN108848300 A CN 108848300A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/63—Control of cameras or camera modules by using electronic viewfinders
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/46—Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
- G06V10/462—Salient features, e.g. scale invariant feature transforms [SIFT]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/64—Computer-aided capture of images, e.g. transfer from script file into camera, check of taken image quality, advice or proposal for image composition or decision on when to take image
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- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Computer Vision & Pattern Recognition (AREA)
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- General Physics & Mathematics (AREA)
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- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The embodiment of the present application discloses the method and apparatus for output information.One specific embodiment of the above method includes：Obtain the image of image acquisition device；Image recognition is carried out to the image got, determines the object for including in the image got；Determine the type of above-mentioned object；The image that at least one includes the object of the above-mentioned type is chosen from preset image collection；The selected image of output.The embodiment can be used for that user is instructed to take pictures, to obtain the preferable image of shooting quality.
Description
Technical field
The invention relates to Internet technical fields, and in particular to the method and apparatus for output information.
Background technique
With the development of smart phone, smart camera, people are in tourism process to the very fast growth of the demand taken pictures.It is clapping
According to or when self-timer, obtained photo and outstanding photo differs greatly.Above-mentioned difference of the gap one side from color, personage's appearance
It is different, on the other hand from finding a view when taking pictures, be laid out.
Summary of the invention
The embodiment of the present application proposes the method and apparatus for output information.
In a first aspect, the embodiment of the present application provides a kind of method for output information, including：Obtain image collector
Set the image of acquisition；Image recognition is carried out to the image got, determines the object for including in the image got；It determines above-mentioned
The type of object；The image that at least one includes the object of the above-mentioned type is chosen from preset image collection；Selected by output
Image.
In some embodiments, it is above-mentioned chosen from preset image collection at least one include the above-mentioned type object
Image, including：Determine that the image subset of the object in above-mentioned image collection including the above-mentioned type is closed；From the conjunction of above-mentioned image subset
At least two images are chosen, the mutual not phase at least one of following parameter of any two images in above-mentioned at least two images
Together：Acquisition parameters, composition parameter.
In some embodiments, the above method further includes：Extract the feature of image got, obtain fisrt feature to
Amount；For the image in selected image, the feature of the image is extracted, obtains second feature vector；Determine above-mentioned fisrt feature
The matching degree of vector and above-mentioned second feature vector；It is less than preset threshold in response to the above-mentioned matching degree of determination, according to the image
Acquisition parameters and/or composition parameter generate shooting advisory information；Export above-mentioned shooting advisory information.
In some embodiments, above-mentioned image collection is obtained by following steps：Crawl be published on network image and
Obtain the comment information for being directed to grabbed image；Sentiment analysis is carried out to above-mentioned comment information, whether determines above-mentioned comment information
For front comment；It is front comment in response to the above-mentioned comment information of determination, above-mentioned image collection is added in grabbed image.
In some embodiments, above-mentioned image collection includes that at least one image subset is closed, and image subset is shared in storage
Image including same type object；And it is above-mentioned in response to the above-mentioned comment information of determination be front comment, by grabbed image
Above-mentioned image collection is added, including：It is front comment in response to the above-mentioned comment information of determination, image knowledge is carried out to grabbed image
Not, the object for including in grabbed image is determined；Determine the type for the object for including in grabbed image；According to identified class
Type grabbed image is added in the image subset conjunction for being used to store the image including corresponding types object.
Second aspect, the embodiment of the present application provide a kind of device for output information, including：Image acquisition unit,
It is configured to obtain the image of image acquisition device；Image identification unit is configured to carry out figure to the image got
As identification, the object for including in the image got is determined；Type determining units are configured to determine the type of above-mentioned object；
Image selection unit is configured to choose the image that at least one includes the object of the above-mentioned type from preset image collection；
Image output unit is configured to export selected image.
In some embodiments, above-mentioned image selection unit includes：Subclass determining module is configured to determine above-mentioned figure
It include the image subset conjunction of the object of the above-mentioned type in image set conjunction；Image chooses module, is configured to close from above-mentioned image subset
Middle selection at least two images, any two images in above-mentioned at least two images mutual not phase at least one of following parameter
Together：Acquisition parameters, composition parameter.
In some embodiments, above-mentioned apparatus further includes：Feature extraction unit is configured to extract the image got
Feature obtains first eigenvector；It is recommended that generation unit, is configured to extract the image for the image in selected image
Feature, obtain second feature vector；Determine the matching degree of above-mentioned first eigenvector Yu above-mentioned second feature vector；In response to
It determines that above-mentioned matching degree is less than preset threshold, according to the acquisition parameters of the image and/or composition parameter, generates shooting recommendation letter
Breath；Export above-mentioned shooting advisory information.
In some embodiments, above-mentioned image collection with lower unit by being arranged to：Image-capture unit, is configured to
Crawl is published on the image of network and obtains the comment information for being directed to grabbed image；Comment and analysis unit, is configured to pair
Above-mentioned comment information carries out sentiment analysis, determines whether above-mentioned comment information is positive comment；Image adding unit, is configured to
It is front comment in response to the above-mentioned comment information of determination, above-mentioned image collection is added in grabbed image.
In some embodiments, above-mentioned image collection includes that at least one image subset is closed, and image subset is shared in storage
Image including same type object；And above-mentioned image adding unit further comprises：Picture recognition module is configured to ring
Image recognition should be carried out to grabbed image, include in determining grabbed image in determining above-mentioned comment information as front comment
Object；Determination type module is configured to determine the type of the object in grabbed image included；Module, quilt is added in image
It is configured to that grabbed image is added to image for being used to store the image including corresponding types object according to identified type
In set.
The third aspect, the embodiment of the present application provide a kind of server, including：One or more processors；Storage device,
The one or more programs of storage are stored thereon with, when said one or multiple programs are executed by said one or multiple processors,
So that said one or multiple processors realize the method as described in first aspect any embodiment.
Fourth aspect, the embodiment of the present application provide a kind of computer-readable medium, are stored thereon with computer program, should
The method as described in first aspect any embodiment is realized when program is executed by processor.
The method and apparatus provided by the above embodiment for output information of the application, first acquisition image collecting device
Then the image of acquisition carries out image recognition to above-mentioned image, determines the object for including in image.It is next determined that object
Type.Then at least one image including same type object is chosen from image collection.Finally, selected image is defeated
Out.The method and apparatus of the present embodiment can be used for that user is instructed to take pictures, to obtain the preferable image of shooting quality.
Detailed description of the invention
By reading a detailed description of non-restrictive embodiments in the light of the attached drawings below, the application's is other
Feature, objects and advantages will become more apparent upon：
Fig. 1 is that this application can be applied to exemplary system architecture figures therein；
Fig. 2 is the flow chart according to one embodiment of the method for output information of the application；
Fig. 3 is the schematic diagram according to an application scenarios of the method for output information of the application；
Fig. 4 is the flow chart according to another embodiment of the method for output information of the application；
Fig. 5 is the structural schematic diagram according to one embodiment of the device for output information of the application；
Fig. 6 is adapted for the structural schematic diagram for the computer system for realizing the server of the embodiment of the present application.
Specific embodiment
The application is described in further detail with reference to the accompanying drawings and examples.It is understood that this place is retouched
The specific embodiment stated is used only for explaining related invention, rather than the restriction to the invention.It also should be noted that in order to
Convenient for description, part relevant to related invention is illustrated only in attached drawing.
It should be noted that in the absence of conflict, the features in the embodiments and the embodiments of the present application can phase
Mutually combination.The application is described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.
Fig. 1 is shown can be using the method for output information of the application or the implementation of the device for output information
The exemplary system architecture 100 of example.
As shown in Figure 1, system architecture 100 may include image collecting device 101,102,103, network 104 and server
105.Network 104 between image collecting device 101,102,103 and server 105 to provide the medium of communication link.Net
Network 104 may include various connection types, such as wired, wireless communication link or fiber optic cables etc..
User can be used image collecting device 101,102,103 and be interacted by network 104 with server 105, to receive
Or send message etc..Various telecommunication customer end applications, such as camera shooting class can be installed on image collecting device 101,102,103
Using, image processing class application, social platform software etc..
Image collecting device 101,102,103 can be hardware, be also possible to software.When image collecting device 101,102,
103 when being hardware, can be with display screen and support the various electronic equipments of Image Acquisition, including but not limited to intelligent phase
Machine, intelligent camera, smart phone, tablet computer, pocket computer on knee etc..When image collecting device 101,102,
103 when being software, may be mounted in above-mentioned cited electronic equipment.Multiple softwares or software module may be implemented into it
(such as providing Distributed Services), also may be implemented into single software or software module.It is not specifically limited herein.
Server 105 can be to provide the server of various services, such as acquire to image collecting device 101,102,103
Image provide support background server.Background server can carry out the data such as the image received the processing such as analyzing,
And processing result (such as image) is fed back into image collecting device 101,102,103.
It should be noted that the method provided by the embodiment of the present application for output information is generally held by server 105
Row, correspondingly, the device for output information is generally positioned in server 105.
It should be noted that server can be hardware, it is also possible to software.When server is hardware, may be implemented
At the distributed server cluster that multiple servers form, individual server also may be implemented into.It, can when server is software
To be implemented as multiple softwares or software module (such as providing Distributed Services), single software or software also may be implemented into
Module.It is not specifically limited herein.
It should be understood that the number of image collecting device, network and server in Fig. 1 is only schematical.According to reality
It now needs, can have any number of image collecting device, network and server.
With continued reference to Fig. 2, the process of one embodiment of the method for output information according to the application is shown
200.The method for output information of the present embodiment, includes the following steps：
Step 201, the image of image acquisition device is obtained.
In the present embodiment, can lead to for the executing subject of the method for output information (such as server shown in FIG. 1)
It crosses wired connection mode or radio connection and receive from image collecting device of Image Acquisition using it from user and scheme
Picture.Above-mentioned image can be the image in the view-finder of image collecting device, be also possible to stored in image collecting device
Image.Above-mentioned image may include at least one object, and above-mentioned object can be building, personage, landscape, plant etc..
It should be pointed out that above-mentioned radio connection can include but is not limited to 3G/4G connection, WiFi connection, bluetooth
Connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection and other currently known or exploitations in the future
Radio connection.
Step 202, image recognition is carried out to the image got, determines the object for including in the image got.
Executing subject can carry out image recognition to above-mentioned image, be wrapped with determining in image after getting above-mentioned image
The object included.Image recognition refers to be handled image, analyzed and is understood using computer, to identify various different modes
The technology of target and object.Industrial image shot by camera can generally be used, then recycle software according to image gray-scale level difference do into
One step identifying processing.Executing subject can carry out image recognition to the image got using existing software, and know in image
The object for including in available image after not.Above-mentioned object can be same type of object, be also possible to it is different types of
Object.For example, can not only include personage in image, but also including building.Alternatively, only including plant in image.
Step 203, the type of above-mentioned object is determined.
After the object that executing subject has included in image has been determined, the type of object can be determined.The type of object can be with
Including building, personage, landscape, plant etc..For example, it includes face and flower that executing subject, which determines in image, then can determine pair
The type of elephant includes personage and plant.
Step 204, the image that at least one includes the object of the above-mentioned type is chosen from preset image collection.
For executing subject after the type of object has been determined, it includes upper that at least one can be chosen from preset image collection
State the image of the object of type.For example, executing subject identifies that the type for the object for including in image is personage and plant, then may be used
To select at least one same image including personage and plant from above-mentioned image collection.
Above-mentioned image collection may include multiple images, the type of the object for including in every image can it is identical can also be with
Difference may include the object of at least one type in every image.Image in above-mentioned image collection can be by technical staff
It screens and determines from multiple images, be also possible to all images issued on a certain website.
Image in above-mentioned image collection can be acquisition parameters, composition parameter or shooting effect preferably image.Shooting
The parameter that uses when parameter refers to shooting photo, such as shutter, aperture, sensitivity, light exposure, whether open flash lamp.Shooting ginseng
Number can be obtained by image collecting device, can also be found by photo files.Composition parameter refers to for describing image
The parameter of composition, such as mode of composition (trichotomy, symmetrical, cross, horizontal line), key position value are (such as three branches, symmetrical
Axis, central point etc.), viewfinder range, color etc..
In some optional implementations of the present embodiment, above-mentioned steps 204 can specifically include unshowned in Fig. 2
Following steps：Firstly, determining that the image subset of the object in image collection including the above-mentioned type is closed.Then, from above-mentioned image
At least two images are chosen in set, wherein any two images in above-mentioned at least two images are at least one of following parameter
It is upper different：Acquisition parameters, composition parameter.
When choosing image, executing subject can determine image of the object in image collection including the above-mentioned type first
Set.Then at least two images are chosen from the conjunction of above-mentioned image subset, wherein any two in above-mentioned at least two images
The different perhaps composition parameter differences of the acquisition parameters of image or acquisition parameters and composition parameter are all different.
Step 205, selected image is exported.
After executing subject chooses an at least image in image collection, selected image can be exported, so that
Above-mentioned image can be shown in the display screen of image collecting device.Then user can by the image that is shown in display screen come
The acquisition parameters or composition parameter of image collecting device are adjusted, to obtain more outstanding image.
With continued reference to the signal that Fig. 3, Fig. 3 are according to the application scenarios of the method for output information of the present embodiment
Figure.In the application scenarios of Fig. 3, user takes pictures to rose using " camera " application installed in smart phone.Intelligence
Image in view-finder is sent to server by mobile phone, and server after image recognition, is determining the object for including in image
For flower.Then the type for determining the object for including in image is plant (or rose), and then selection includes from image collection
The image of rose.It finally outputs three and includes the image of rose, and image is shown under smart phone view-finder
Side, for user's browsing.User is after browsing following three images, the position of adjustable smart phone, to adjust to rose
Colored shooting angle obtains the preferable image of shooting effect.
The method provided by the above embodiment for output information of the application obtains image acquisition device first
Then image carries out image recognition to above-mentioned image, determines the object for including in image.It is next determined that the type of object.So
At least one image including same type object is chosen from image collection afterwards.Finally, selected image is exported.This reality
The method for applying example can be used for that user is instructed to take pictures, to obtain the preferable image of shooting quality.
In some optional implementations of the present embodiment, above-mentioned image collection can by Fig. 2 it is unshowned with
Lower step obtains：Firstly, crawl is published on the image of network and obtains the comment information for being directed to grabbed image.Then, right
Comment information carries out sentiment analysis, determines whether above-mentioned comment information is positive comment.Finally, believing in response to the above-mentioned comment of determination
Breath is front comment, and image collection is added in grabbed image.
In this implementation, executing subject can grab the figure for being published on network by web crawlers (also known as webpage spider)
Picture.Specifically, executing subject can grab the image for being published on some or multiple appointed websites.For example, executing subject can be with
The image of crawl publication Mr. Yu well-known image comment website, or obtain the prize-winning image of publication Mr. Yu's image forum.
Meanwhile executing subject can also obtain the comment information for grabbed image.Above-mentioned comment information can be use
Family deliver for image, information including text or expression.It is understood that above-mentioned comment information may have it is a plurality of,
The available wherein comment of executing subject.This comment can be what certain well-known image comment personnel were issued, can also be with
It is the comment of image publisher.
Then, executing subject can to above-mentioned comment information carry out sentiment analysis, with the above-mentioned comment information of determination whether be
Front comment.Sentiment analysis (Sentiment analysis), also known as proneness analysis are to the subjectivity for having emotional color
Text is analyzed, handled, concluded and the process of reasoning.That is, by carrying out sentiment analysis to comment information, it can be true
Whether determine in comment information comprising positive mood.Positive mood refers to the positive mood of one kind of people, happy, optimistic, self-confident, glad
Appreciate, loosen etc..If including positive mood, then it is assumed that the comment information is front comment.
Determine comment information for front comment after, it can be assumed that the image grabbed be outstanding image, so as to will
Grabbed image is added in image collection.
In some optional implementations of the present embodiment, above-mentioned image collection may include multiple images subclass,
It includes the image of same type object that image subset, which is shared in storage,.Then executing subject can also will be grabbed by following steps
Image collection is added in image：Firstly, being front comment in response to the above-mentioned comment information of determination, image knowledge is carried out to grabbed image
Not, the object for including in grabbed image is determined.Then, it is determined that the type for the object for including in grabbed image.Finally, according to
Identified type grabbed image is added in the image subset conjunction for being used to store the image including corresponding types object.
In this implementation, after determining comment information for front comment, image recognition can be carried out to grabbed image,
To determine the object for including in grabbed image.Then the type for the object for including in grabbed image is determined.Finally, by being grabbed
Image is taken to be added in the image subset conjunction of the image of corresponding types object.For example, grabbed image is high building image, to the figure
After carrying out image recognition, determine that the object for including in the image is high building.Then the type for determining object is " building ", then will
The image is added in the image subset conjunction in image collection for the image that storage object type is " building ".
With continued reference to Fig. 4, it illustrates the streams according to another embodiment of the method for output information of the application
Journey 400.As shown in figure 4, can also include following step after choosing at least one image in image collection in the present embodiment
Suddenly：
Step 401, the feature for extracting the image got, obtains first eigenvector.
Executing subject can extract the feature of the image got using various feasible modes, obtain fisrt feature to
Amount.For example, executing subject can extract the feature of the image got using feature extraction algorithm, such as SIFT algorithm (Scale
Invariant Feature Transform, Scale invariant features transform matching), ORB algorithm (《ORB:an efficient
alternative to SIFT or SURF》It is to be proposed in the paper that Rublee et al. is delivered on ICCV in 2011
), FREAK algorithm (《FREAK:Fast Retina Keypoint》It is to be proposed on a paper on CVPR in 2012
) etc..Alternatively, executing subject extracts the feature of the image got using the convolutional neural networks after training.It is special extracting
After sign, the available binary system to extracted feature is described, i.e. first eigenvector.
Then, step 402 is executed for selected image.Step 402 may further include following sub-step：
Sub-step 4021 extracts the feature of the image for the image in selected image, obtains second feature vector.
In the present embodiment, executing subject can be used and feature extraction algorithm same in step 401 or convolutional Neural net
Network to carry out feature extraction to each image in selected image.For each image in selected image,
To obtain second feature vector.
Sub-step 4022 determines the matching degree of first eigenvector Yu second feature vector.
After determining the first eigenvector of image and the second feature vector of grabbed image that get, it can calculate
The matching degree of the two.Herein, matching degree can be indicated with the distance between first eigenvector and second feature vector.
Sub-step 4023, in response to determining that matching degree is less than preset threshold, according to the acquisition parameters and/or composition of the image
Parameter generates shooting advisory information.
When above-mentioned matching degree is less than preset threshold, illustrate the image got with selected image difference away from larger.By
It is preset outstanding image in selected image, then can be come according to the acquisition parameters and/or composition parameter of selected image
Generate shooting advisory information.Shooting advisory information refers to the information for instructing user to shoot, and may include icon or text.
Above-mentioned shooting advisory information can be the acquisition parameters and/or composition parameter of selected image, can also be what comparison was got
The information that the acquisition parameters of image, the acquisition parameters of composition parameter and selected image, composition parameter obtain.For example, above-mentioned bat
Taking the photograph advisory information can be " it is recommended that view finder is mobile to upper left side ", or " shine the whole body of personage and become half body photograph " etc..On
Stating shooting advisory information can also be icon, for example, be directed toward upper left arrow, to prompt user by view finder to upper left side
It is mobile.
Sub-step 4024, output shooting advisory information.
After obtaining above-mentioned shooting advisory information, above-mentioned shooting advisory information can be exported, so that user passes through image
Acquisition device is checked.
The method provided by the above embodiment for output information of the application, more intuitively can provide shooting for user
Advisory information allows the user to the higher image of faster shooting quality.
With further reference to Fig. 5, as the realization to method shown in above-mentioned each figure, this application provides one kind for exporting letter
One embodiment of the device of breath, the Installation practice is corresponding with embodiment of the method shown in Fig. 2, which can specifically answer
For in various electronic equipments.
As shown in figure 5, the device 500 for output information of the present embodiment includes image acquisition unit 501, image recognition
Unit 502, type determining units 503, image selection unit 504 and image output unit 505.
Image acquisition unit 501 is configured to obtain the image of image acquisition device.
Image identification unit 502 is configured to carry out image recognition to the image got, determine in the image got
Including object.
Type determining units 503 are configured to determine the type of above-mentioned object.
Image selection unit 504, being configured to choose at least one from preset image collection includes the above-mentioned type
The image of object.
Image output unit 505 is configured to export selected image.
In some optional implementations of the present embodiment, above-mentioned image selection unit 504 may further include Fig. 5
In unshowned subclass determining module and image choose module.
Wherein, subclass determining module is configured to determine image of the object in image collection including the above-mentioned type
Set.
Image chooses module, is configured to choose at least two images from the conjunction of above-mentioned image subset, above-mentioned at least two
Any two images in image are different at least one of following parameter：Acquisition parameters, composition parameter.
In some optional implementations of the present embodiment, above-mentioned apparatus 500, which can further include in Fig. 5, not to be shown
Feature extraction unit and suggestion generation unit out.
Wherein, feature extraction unit is configured to extract the feature of the image got, obtains first eigenvector.
It is recommended that generation unit, is configured to extract the image in selected image the feature of the image, obtains second
Feature vector；Determine the matching degree of first eigenvector Yu second feature vector；In response to determining that matching degree is less than preset threshold,
According to the acquisition parameters of the image and/or composition parameter, shooting advisory information is generated；Output shooting advisory information.
In some optional implementations of the present embodiment, above-mentioned image collection can pass through figure unshowned in Fig. 5
As picking unit, comment and analysis unit and image adding unit configure to obtain.
Wherein, image-capture unit is configured to grab the image for being published on network and obtains for grabbed image
Comment information.
Comment and analysis unit is configured to carry out sentiment analysis to comment information, determines whether above-mentioned comment information is positive
Face comment.
Image adding unit is configured in response to determine that for front comment, grabbed image is added for above-mentioned comment information
Enter image collection.
In some optional implementations of the present embodiment, above-mentioned image collection may include at least one image subset
It closes, it includes the image of same type object that image subset, which is shared in storage,.Above-mentioned image adding unit may further include figure
As module is added in identification module, determination type module and image.
Picture recognition module, be configured in response to determine above-mentioned comment information for front comment, to grabbed image into
Row image recognition determines the object for including in grabbed image.
Determination type module is configured to determine the type of the object in grabbed image included.
Module is added in image, is configured to according to identified type, it includes pair that the addition of grabbed image, which is used to store,
It answers in the image subset conjunction of the image of type object.
The device provided by the above embodiment for output information of the application obtains image acquisition device first
Then image carries out image recognition to above-mentioned image, determines the object for including in image.It is next determined that the type of object.So
At least one image including same type object is chosen from image collection afterwards.Finally, selected image is exported.This reality
The device for applying example can be used for that user is instructed to take pictures, to obtain the preferable image of shooting quality.
It should be appreciated that the unit 501 for recording in the device 500 of output information is to unit 505 respectively and in reference Fig. 2
Each step in the method for description is corresponding.As a result, above with respect to the operation and feature of the method description for output information
It is equally applicable to device 500 and unit wherein included, details are not described herein.
Below with reference to Fig. 6, it illustrates the computer systems 600 for the server for being suitable for being used to realize the embodiment of the present application
Structural schematic diagram.Server shown in Fig. 6 is only an example, should not function and use scope band to the embodiment of the present application
Carry out any restrictions.
As shown in fig. 6, computer system 600 includes central processing unit (CPU) 601, it can be read-only according to being stored in
Program in memory (ROM) 602 or be loaded into the program in random access storage device (RAM) 603 from storage section 608 and
Execute various movements appropriate and processing.In RAM 603, also it is stored with system 600 and operates required various programs and data.
CPU 601, ROM 602 and RAM 603 are connected with each other by bus 604.Input/output (I/O) interface 605 is also connected to always
Line 604.
I/O interface 605 is connected to lower component：Importation 606 including keyboard, mouse etc.；It is penetrated including such as cathode
The output par, c 607 of spool (CRT), liquid crystal display (LCD) etc. and loudspeaker etc.；Storage section 608 including hard disk etc.；
And the communications portion 609 of the network interface card including LAN card, modem etc..Communications portion 609 via such as because
The network of spy's net executes communication process.Driver 610 is also connected to I/O interface 605 as needed.Detachable media 611, such as
Disk, CD, magneto-optic disk, semiconductor memory etc. are mounted on as needed on driver 610, in order to read from thereon
Computer program be mounted into storage section 608 as needed.
Particularly, in accordance with an embodiment of the present disclosure, it may be implemented as computer above with reference to the process of flow chart description
Software program.For example, embodiment of the disclosure includes a kind of computer program product comprising carrying is on a machine-readable medium
Computer program, which includes the program code for method shown in execution flow chart.In such implementation
In example, which can be downloaded and installed from network by communications portion 609, and/or from detachable media 611
It is mounted.When the computer program is executed by central processing unit (CPU) 601, limited in execution the present processes upper
State function.
It should be noted that computer-readable medium described herein can be computer-readable signal media or
Computer readable storage medium either the two any combination.Computer readable storage medium for example can be --- but
Be not limited to --- electricity, magnetic, optical, electromagnetic, infrared ray or semiconductor system, device or device, or any above combination.
The more specific example of computer readable storage medium can include but is not limited to：Electrical connection with one or more conducting wires,
Portable computer diskette, hard disk, random access storage device (RAM), read-only memory (ROM), erasable type may be programmed read-only deposit
Reservoir (EPROM or flash memory), optical fiber, portable compact disc read-only memory (CD-ROM), light storage device, magnetic memory
Part or above-mentioned any appropriate combination.
In this application, computer readable storage medium can be any tangible medium for including or store program, the journey
Sequence can be commanded execution system, device or device use or in connection.And in this application, it is computer-readable
Signal media may include in a base band or as carrier wave a part propagate data-signal, wherein carrying computer can
The program code of reading.The data-signal of this propagation can take various forms, including but not limited to electromagnetic signal, optical signal or
Above-mentioned any appropriate combination.Computer-readable signal media can also be any other than computer readable storage medium
Computer-readable medium, the computer-readable medium can send, propagate or transmit for by instruction execution system, device or
Person's device uses or program in connection.The program code for including on computer-readable medium can be with any appropriate
Medium transmission, including but not limited to：Wirelessly, electric wire, optical cable, RF etc. or above-mentioned any appropriate combination.
The calculating of the operation for executing the application can be write with one or more programming languages or combinations thereof
Machine program code, above procedure design language include object oriented program language-such as Java, Smalltalk, C+
+, it further include conventional procedural programming language-such as " C " language or similar programming language.Program code can
Fully to execute, partly execute on the user computer on the user computer, be executed as an independent software package,
Part executes on the remote computer or executes on a remote computer or server completely on the user computer for part.
In situations involving remote computers, remote computer can pass through the network of any kind --- including local area network (LAN)
Or wide area network (WAN)-is connected to subscriber computer, or, it may be connected to outer computer (such as utilize Internet service
Provider is connected by internet).
Flow chart and block diagram in attached drawing are illustrated according to the system of the various embodiments of the application, method and computer journey
The architecture, function and operation in the cards of sequence product.In this regard, each box in flowchart or block diagram can generation
A part of one module, program segment or code of table, a part of the module, program segment or code include one or more use
The executable instruction of the logic function as defined in realizing.It should also be noted that in some implementations as replacements, being marked in box
The function of note can also occur in a different order than that indicated in the drawings.For example, two boxes succeedingly indicated are actually
It can be basically executed in parallel, they can also be executed in the opposite order sometimes, and this depends on the function involved.Also it to infuse
Meaning, the combination of each box in block diagram and or flow chart and the box in block diagram and or flow chart can be with holding
The dedicated hardware based system of functions or operations as defined in row is realized, or can use specialized hardware and computer instruction
Combination realize.
Being described in unit involved in the embodiment of the present application can be realized by way of software, can also be by hard
The mode of part is realized.Described unit also can be set in the processor, for example, can be described as：A kind of processor packet
Include image acquisition unit, image identification unit, type determining units, image selection unit and image output unit.Wherein, these
The title of unit does not constitute the restriction to the unit itself under certain conditions, for example, image acquisition unit can also be retouched
It states as " unit for obtaining the image of image acquisition device ".
As on the other hand, present invention also provides a kind of computer-readable medium, which be can be
Included in device described in above-described embodiment；It is also possible to individualism, and without in the supplying device.Above-mentioned calculating
Machine readable medium carries one or more program, when said one or multiple programs are executed by the device, so that should
Device：Obtain the image of image acquisition device；Image recognition is carried out to the image got, is determined in the image got
Including object；Determine the type of above-mentioned object；At least one pair including the above-mentioned type is chosen from preset image collection
The image of elephant；The selected image of output.
Above description is only the preferred embodiment of the application and the explanation to institute's application technology principle.Those skilled in the art
Member is it should be appreciated that invention scope involved in the application, however it is not limited to technology made of the specific combination of above-mentioned technical characteristic
Scheme, while should also cover in the case where not departing from foregoing invention design, it is carried out by above-mentioned technical characteristic or its equivalent feature
Any combination and the other technical solutions formed.Such as features described above has similar function with (but being not limited to) disclosed herein
Can technical characteristic replaced mutually and the technical solution that is formed.
Claims (12)
1. a kind of method for output information, including：
Obtain the image of image acquisition device；
Image recognition is carried out to the image got, determines the object for including in the image got；
Determine the type of the object；
The image that at least one includes the object of the type is chosen from preset image collection；
The selected image of output.
2. according to the method described in claim 1, wherein, described at least one is chosen from preset image collection includes described
The image of the object of type, including：
Determine that the image subset of the object in described image set including the type is closed；
At least two images are chosen from described image subclass, any two images at least two images are following
It is different at least one parameter：Acquisition parameters, composition parameter.
3. according to the method described in claim 1, wherein, the above method further includes：
The feature for extracting the image got, obtains first eigenvector；
For the image in selected image, the feature of the image is extracted, obtains second feature vector；Determine the fisrt feature
The matching degree of vector and the second feature vector；It is less than preset threshold in response to the determination matching degree, according to the image
Acquisition parameters and/or composition parameter generate shooting advisory information；Export the shooting advisory information.
4. according to the method described in claim 1, wherein, described image set is obtained by following steps：
Crawl is published on the image of network and obtains the comment information for being directed to grabbed image；
Sentiment analysis is carried out to the comment information, determines whether the comment information is positive comment；
It is front comment in response to the determination comment information, described image set is added in grabbed image.
5. according to the method described in claim 4, wherein, described image set includes that at least one image subset is closed, image
Set is for storing the image including same type object；And
It is described to be commented in response to the determination comment information for front, described image set is added in grabbed image, including：
It is front comment in response to the determination comment information, image recognition is carried out to grabbed image, determines grabbed image
In include object；
Determine the type for the object for including in grabbed image；
According to identified type, grabbed image is added to the image subset for being used for storing the image including corresponding types object
In conjunction.
6. a kind of device for output information, including：
Image acquisition unit is configured to obtain the image of image acquisition device；
Image identification unit is configured to carry out the image got image recognition, includes in the determining image got
Object；
Type determining units are configured to determine the type of the object；
Image selection unit is configured to choose the figure that at least one includes the object of the type from preset image collection
Picture；
Image output unit is configured to export selected image.
7. device according to claim 6, wherein described image selection unit includes：
Subclass determining module, the image subset for being configured to determine the object in described image set including the type are closed；
Image chooses module, is configured to choose at least two images, at least two images from described image subclass
In any two images it is different at least one of following parameter：Acquisition parameters, composition parameter.
8. device according to claim 6, wherein described device further includes：
Feature extraction unit is configured to extract the feature of the image got, obtains first eigenvector；
It is recommended that generation unit, is configured to extract the image in selected image the feature of the image, obtains second feature
Vector；Determine the matching degree of the first eigenvector Yu the second feature vector；It is less than in response to the determination matching degree
Preset threshold generates shooting advisory information according to the acquisition parameters of the image and/or composition parameter；The shooting is exported to suggest
Information.
9. device according to claim 6, wherein described image set with lower unit by being arranged to：
Image-capture unit is configured to grab the image for being published on network and obtains the comment letter for grabbed image
Breath；
Comment and analysis unit is configured to carry out sentiment analysis to the comment information, determines whether the comment information is positive
Face comment；
Image adding unit is configured in response to determine that for front comment, institute is added in grabbed image by the comment information
State image collection.
10. device according to claim 9, wherein described image set includes that at least one image subset is closed, image
Set is for storing the image including same type object；And
Described image adding unit further comprises：
Picture recognition module is configured in response to determine that the comment information for front comment, carries out figure to grabbed image
As identification, the object for including in grabbed image is determined；
Determination type module is configured to determine the type of the object in grabbed image included；
Module is added in image, is configured to according to identified type, it includes corresponding class that the addition of grabbed image, which is used to store,
During the image subset of the image of type object is closed.
11. a kind of server, including：
One or more processors；
Storage device is stored thereon with one or more programs,
When one or more of programs are executed by one or more of processors, so that one or more of processors are real
Now such as method as claimed in any one of claims 1 to 5.
12. a kind of computer-readable medium, is stored thereon with computer program, wherein the realization when program is executed by processor
Such as method as claimed in any one of claims 1 to 5.
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Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090040324A1 (en) * | 2007-08-10 | 2009-02-12 | Osamu Nonaka | Imaging apparatus, imaging system, and imaging method |
| US20090059017A1 (en) * | 2007-08-29 | 2009-03-05 | Sanyo Electric Co., Ltd. | Imaging device and image processing apparatus |
| CN101782898A (en) * | 2010-03-25 | 2010-07-21 | 中国科学院计算技术研究所 | Method for analyzing tendentiousness of affective words |
| US20110090390A1 (en) * | 2009-10-15 | 2011-04-21 | Tomoya Narita | Information processing apparatus, display control method, and display control program |
| CN102591868A (en) * | 2011-01-10 | 2012-07-18 | 株式会社理光 | System and method for automatic generation of photograph guide |
| CN103870138A (en) * | 2012-12-11 | 2014-06-18 | 联想(北京)有限公司 | Information processing method and electronic equipment |
| CN104301613A (en) * | 2014-10-16 | 2015-01-21 | 深圳市中兴移动通信有限公司 | Mobile terminal and photographing method thereof |
| CN106027902A (en) * | 2016-06-24 | 2016-10-12 | 依偎科技（南昌）有限公司 | Photographing method and mobile terminal |
| CN106022878A (en) * | 2016-05-19 | 2016-10-12 | 华南理工大学 | Community comment emotion tendency analysis-based mobile phone game ranking list construction method |
| CN106034206A (en) * | 2015-03-17 | 2016-10-19 | 联想(北京)有限公司 | Electronic equipment and image display method |
| CN106161939A (en) * | 2016-07-27 | 2016-11-23 | 北京锤子数码科技有限公司 | A kind of method, photo taking and terminal |
| CN107343142A (en) * | 2017-06-19 | 2017-11-10 | 上海传英信息技术有限公司 | The image pickup method and filming apparatus of a kind of photo |
| CN107347135A (en) * | 2017-06-20 | 2017-11-14 | 北京小米移动软件有限公司 | Take pictures processing method, device and terminal device |
| CN107395965A (en) * | 2017-07-14 | 2017-11-24 | 维沃移动通信有限公司 | A kind of image processing method and mobile terminal |
| CN107493426A (en) * | 2017-07-05 | 2017-12-19 | 努比亚技术有限公司 | A kind of information collecting method, equipment and computer-readable recording medium |
| CN107730445A (en) * | 2017-10-31 | 2018-02-23 | 广东欧珀移动通信有限公司 | Image processing method, device, storage medium and electronic equipment |
-
2018
- 2018-05-08 CN CN201810429487.3A patent/CN108848300A/en active Pending
Patent Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090040324A1 (en) * | 2007-08-10 | 2009-02-12 | Osamu Nonaka | Imaging apparatus, imaging system, and imaging method |
| US20090059017A1 (en) * | 2007-08-29 | 2009-03-05 | Sanyo Electric Co., Ltd. | Imaging device and image processing apparatus |
| US20110090390A1 (en) * | 2009-10-15 | 2011-04-21 | Tomoya Narita | Information processing apparatus, display control method, and display control program |
| CN101782898A (en) * | 2010-03-25 | 2010-07-21 | 中国科学院计算技术研究所 | Method for analyzing tendentiousness of affective words |
| CN102591868A (en) * | 2011-01-10 | 2012-07-18 | 株式会社理光 | System and method for automatic generation of photograph guide |
| CN103870138A (en) * | 2012-12-11 | 2014-06-18 | 联想(北京)有限公司 | Information processing method and electronic equipment |
| CN104301613A (en) * | 2014-10-16 | 2015-01-21 | 深圳市中兴移动通信有限公司 | Mobile terminal and photographing method thereof |
| CN106034206A (en) * | 2015-03-17 | 2016-10-19 | 联想(北京)有限公司 | Electronic equipment and image display method |
| CN106022878A (en) * | 2016-05-19 | 2016-10-12 | 华南理工大学 | Community comment emotion tendency analysis-based mobile phone game ranking list construction method |
| CN106027902A (en) * | 2016-06-24 | 2016-10-12 | 依偎科技（南昌）有限公司 | Photographing method and mobile terminal |
| CN106161939A (en) * | 2016-07-27 | 2016-11-23 | 北京锤子数码科技有限公司 | A kind of method, photo taking and terminal |
| CN107343142A (en) * | 2017-06-19 | 2017-11-10 | 上海传英信息技术有限公司 | The image pickup method and filming apparatus of a kind of photo |
| CN107347135A (en) * | 2017-06-20 | 2017-11-14 | 北京小米移动软件有限公司 | Take pictures processing method, device and terminal device |
| CN107493426A (en) * | 2017-07-05 | 2017-12-19 | 努比亚技术有限公司 | A kind of information collecting method, equipment and computer-readable recording medium |
| CN107395965A (en) * | 2017-07-14 | 2017-11-24 | 维沃移动通信有限公司 | A kind of image processing method and mobile terminal |
| CN107730445A (en) * | 2017-10-31 | 2018-02-23 | 广东欧珀移动通信有限公司 | Image processing method, device, storage medium and electronic equipment |
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