CN111931649A - Face recognition method and system in video conference process - Google Patents
Face recognition method and system in video conference process Download PDFInfo
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- CN111931649A CN111931649A CN202010797869.9A CN202010797869A CN111931649A CN 111931649 A CN111931649 A CN 111931649A CN 202010797869 A CN202010797869 A CN 202010797869A CN 111931649 A CN111931649 A CN 111931649A
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- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
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Abstract
The invention discloses a face recognition method and a face recognition system in a video conference process, wherein the method comprises the following steps: after a face recognition module and a first face matching module of a client are started, the face recognition module recognizes face information in a video stream of the client and records the positions of all faces, display positions of personnel information corresponding to all face information are determined according to the positions of all faces, and face information is extracted; the first face matching module matches the face information extracted by the face recognition module with a first database prestored in the local end of the client; and displaying the personnel information corresponding to the face information after the matching is successful. The face recognition method and the face recognition system in the video conference process have the advantages of low occupied network bandwidth, good real-time performance and support of super-large concurrency.
Description
Technical Field
The present invention relates to the field of video communication technologies, and in particular, to a method and a system for face recognition during a video conference.
Background
In the video conference process, sometimes, for the purposes of facilitating personnel communication and ensuring conference safety and the like, the face information needs to be recognized in real time, and the current real-time recognition of the face information mainly comprises two modes: the method comprises the steps that firstly, videos are uploaded in real time, real-time identification and personnel information matching are carried out through a face identification service, and then matching results are returned; and secondly, uploading the I frame information at regular time, performing real-time identification and personnel information matching by face identification and face matching services, and then returning a matching result at regular time.
The inventors have found that the following disadvantages exist in the two current ways:
the first scheme is that the real-time uploading of the video occupies a large amount of bandwidth, the server needs to continuously identify and match, the resource consumption is large, the first login verification is more applicable, in the video conference, the number of participants is large, particularly when each participant selects to watch different target pictures and needs to identify the personnel in the pictures, hundreds of paths of video streams need to be identified in one conference, and the server is difficult to meet or has a high cost.
The second scheme of uploading picture information at regular time and then matching personnel information by face recognition and matching service does save bandwidth, but when hundreds of video streams in a single conference need to be recognized, hundreds of face recognition links need to be maintained in real time, a large amount of transmitted I frame information occupies bandwidth, consumes resources, and due to the delay problem, when a server returns personnel position and matching information, the personnel may leave the original position, and at the moment, when the name of the personnel is displayed, the position may be deviated, for example, the name of Zhang III is displayed on the head of Li IV, or is an empty item, or the displayed position shields the face or appears in other improper positions.
The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.
Disclosure of Invention
The invention aims to provide a face recognition system in a video conference process, which occupies lower network bandwidth and has good real-time performance and supports super-large concurrency in the real-time face recognition process.
In order to achieve the above object, the present invention provides a face recognition method in a video conference process, which comprises: after a face recognition module of a local end of a client and a first face matching module of the local end are started, the face recognition module recognizes face information in a video stream of the client and records the positions of all faces, the display positions of personnel information corresponding to all face information are determined according to the positions of all faces, and the face information is extracted; the first face matching module matches the face information extracted by the face recognition module with a first database prestored in the local end of the client; and if the first database stores the personnel information corresponding to the certain face information, the first face matching module judges that the face information is successfully matched and displays the personnel information corresponding to the face information at the display position of the personnel information.
In an embodiment of the present invention, the face recognition method further includes: if the first database does not store the personnel information corresponding to the face information, the first face matching module judges that the face information fails to be matched; the first face matching module sends face information failed in matching to a server; the server starts a second face matching module of the server side; a second face matching module of the server matches the face information of which the matching of the client fails with a second database prestored in the server; if the second database stores the personnel information corresponding to the certain face information which fails to be matched with the client, the second face matching module judges that the face information is successfully matched, and the server sends the personnel information corresponding to the face information to the first face matching module of the client; and the first face matching module of the client displays the personnel information successfully matched by the server at the corresponding display position of the client according to the display position information of the personnel information determined by the face recognition module.
In an embodiment of the present invention, the face recognition method further includes: and the first face matching module of the client stores the personnel information corresponding to the face information sent by the server to the first database of the local end.
In an embodiment of the present invention, the face recognition method further includes: the first face matching module is used for regularly cleaning the personnel information in the first database according to the personnel information use frequency condition in the first database.
In an embodiment of the present invention, the periodically cleaning the person information in the first database by the first face matching module according to the use frequency of the person information in the first database includes: the first face matching module compares the number of personnel contained in the personnel information in the first database with a preset threshold value, and if the number of personnel is greater than the preset threshold value, the personnel information with low use frequency in the first database is cleaned, so that the number of personnel contained in the cleaned personnel information in the first database is not more than the preset threshold value.
In an embodiment of the present invention, the face recognition method further includes establishing the second database, where the establishing the second database includes: the server extracts the face information of the photo or the video input by the administrator or uploaded by the client, summarizes the face information and the corresponding personnel information and stores the summary into the second database.
Based on the same inventive concept, the invention also provides a face recognition system in the video conference process, which comprises the following steps: the system comprises a first database, a face recognition module and a first face matching module. The first database is arranged at the client and used for storing the personnel information corresponding to the face information. The face recognition module is arranged at the client and used for recognizing face information in the client video stream, recording the positions of the faces, determining the display positions of the personnel information corresponding to the face information according to the positions of the faces, and extracting the face information. The first face matching module is arranged at the client, coupled with the first database and the face recognition module, and used for matching the face information extracted by the face recognition module with a first database pre-stored at the local end of the client, and if the first database stores the personnel information corresponding to the face information, judging that the face information is successfully matched, and displaying the personnel information corresponding to the face information at the display position of the personnel information.
In an embodiment of the present invention, the first face matching module is further configured to determine that matching of the face information fails when the first database does not store the person information corresponding to the face information, and send the face information that fails to be matched to the server.
In an embodiment of the present invention, the face recognition system further includes: a second database and a second face matching module. The second database is arranged at the server end and used for storing the personnel information corresponding to the face information. The second face matching module is arranged at the server end, is coupled with the first face matching module, the face recognition module and the second database, and is used for matching the face information failed in matching at the client end with the second database prestored at the server end; if the second database stores the personnel information corresponding to the certain face information of which the client-side matching fails, the face information is judged to be successfully matched, and the personnel information corresponding to the face information is sent to the first face matching module. The first face matching module is further used for displaying the personnel information successfully matched by the server at the corresponding display position of the client according to the display position information of the personnel information determined by the face recognition module.
Based on the same inventive concept, the invention further provides a computer-readable storage medium, which is used for executing the face recognition method in the video conference process according to any one of the above embodiments.
Compared with the prior art, according to the face recognition method and the face recognition system in the video conference process, the recognition matching service is designed in a distributed mode, namely, the face recognition module and the face matching module are arranged in the client side at the same time, and the client side is responsible for face recognition and face matching work in video streams displayed by the client side.
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FIG. 1 is a block diagram of steps of a face recognition method during a video conference, according to an embodiment of the present invention;
fig. 2 is a block diagram of a face recognition system during a video conference according to an embodiment of the present invention.
Detailed Description
The following detailed description of the present invention is provided in conjunction with the accompanying drawings, but it should be understood that the scope of the present invention is not limited to the specific embodiments.
Throughout the specification and claims, unless explicitly stated otherwise, the word "comprise", or variations such as "comprises" or "comprising", will be understood to imply the inclusion of a stated element or component but not the exclusion of any other element or component.
Fig. 1 is a block diagram of steps of a face recognition method in a video conference process according to an embodiment of the present invention.
In step S100, each client performs face recognition. After each participating client joins the conference, if the face recognition module of the local end and the first face matching module of the local end are started, the face recognition module starts to recognize face information in the video stream of the client and record the position of each face, and determines the display position of the personnel information corresponding to each face information according to the position of each face, and extracts the face information. The personnel information can be personal information such as names, positions, departments and the like. The display position may be a region around the face, such as the crown of the head, the chin, the side of the ear, or the like.
In step S200, each client performs face matching. And the first face matching module of each client matches the face information extracted by the face recognition module with a first database prestored in the local end of the client.
After the client matching is successful in step S310, the staff information is displayed. If the first database stores the personnel information corresponding to the certain face information, the first face matching module judges that the face information is successfully matched and displays the personnel information corresponding to the face information at the display position of the personnel information.
After the client fails to match in step S320, the face information is sent to the server. If the first database does not store the personnel information corresponding to the certain face information, the first face matching module judges that the face information fails to be matched, and the first face matching module sends the face information which fails to be matched to the server.
In step S321, the second face matching module at the server performs face information matching. And the second face matching module matches the face information failed in matching at the client side with a second database prestored at the server side. If the second database stores the personnel information corresponding to the certain face information which fails to be matched with the client, the second face matching module judges that the face information is successfully matched, and the server sends the personnel information corresponding to the face information to the first face matching module of the client. Wherein the second database needs to be pre-established. The library building process is as follows: the server extracts the face information of the photo or the video input by the administrator or uploaded by the client, summarizes the face information and the corresponding personnel information and stores the summary in the second database.
In step S322, the client displays the person information successfully matched by the server. And a first face matching module of the client displays the personnel information successfully matched by the server at the corresponding display position of the client according to the display position information of the personnel information determined by the face recognition module.
In step S323, the client updates the first database of the local end. And a first face matching module of the client stores the personnel information corresponding to the face information sent by the server to a first database of the local terminal.
Preferably, in an embodiment, the face recognition method further includes: the first face matching module regularly cleans the personnel information in the first database according to the personnel information use frequency condition in the first database. Specifically, the first face matching module compares the number of people contained in the person information in the first database with a preset threshold, and if the number of people is greater than the preset threshold, the person information with low use frequency in the first database is cleaned, so that the number of people contained in the person information in the cleaned first database is not more than the preset threshold. The security of personnel information can be ensured through the implementation mode, the complete database is stored in the relatively safe server side, the client side can temporarily store partial matching information, and if the client side can mainly store face information with high frequency, the matching efficiency can be further improved.
Based on the same inventive concept, the present embodiment further provides a face recognition system in a video conference process, as shown in fig. 2, the system includes: the system comprises a first database 10, a face recognition module 11 and a first face matching module 12 which are deployed at a client, and preferably further comprises a second database 20 and a second face matching module 21 which are deployed at a server.
The first database 10 is used for storing the person information corresponding to the face information. Preferably, the first database 10 may set an upper limit of storage, such as storing only information of 10 persons, and storing information of persons with high use frequency with emphasis, so as to improve subsequent face matching efficiency.
The face recognition module 11 is configured to recognize face information in the client video stream, record positions of faces, determine display positions of person information corresponding to the face information according to the positions of the faces, and extract the face information.
The first face matching module 12 is coupled with the first database 10 and the face recognition module 11, and is configured to match the face information extracted by the face recognition module 11 with the first database 10 pre-stored in the local side of the client, and if the first database 10 stores the person information corresponding to the face information, it is determined that the face information is successfully matched, and the person information corresponding to the face information is displayed at the display position of the person information.
The first face matching module 12 is further configured to determine that matching of certain face information fails when the first database 10 does not store the person information corresponding to the face information, and send the face information that fails to match to the server.
The second database 20 is used for storing the person information corresponding to the face information. The second database 20 may store all personnel information that have used the videoconference system. The database building method is that the server extracts the face information of the photo or video input by the administrator or uploaded by the client, and the face information and the corresponding personnel information are collected and stored in the second database 20.
The second face matching module 21 is coupled with the first face matching module 12, the face recognition module 11 and the second database 20, and is used for matching the face information of the client matching failure with the second database 20 prestored in the server; if the second database 20 stores the person information corresponding to the certain face information for which the client matching fails, it is determined that the face information is successfully matched, and the person information corresponding to the face information is sent to the first face matching module 12.
In an embodiment, the first face matching module 12 is further configured to display, according to the display position information of the person information determined by the face recognition module 11, the person information successfully matched by the server at a corresponding display position of the client. And stores the personnel information corresponding to the face information sent by the server into the first database 10 of the local end.
Preferably, the first face matching module 12 is further configured to periodically clean the person information in the first database 10 according to the use frequency condition of the person information in the first database 10, and store the person information with a high use frequency in a focused manner, so as to improve subsequent face matching efficiency. The first face matching module 12 compares the number of people included in the person information in the first database 10 with a preset threshold, and if the number of people is greater than the preset threshold, the person information with low use frequency in the first database 10 is cleaned, so that the number of people included in the person information in the cleaned first database 10 is not more than the preset threshold.
Based on the same inventive concept, the present embodiment also provides a computer-readable storage medium, which can execute the face recognition method of any of the above embodiments.
In summary, the face recognition method and system in the video conference process according to the embodiment adopts a distributed architecture, and divides the service into two parts of face recognition and face matching service, wherein the client part deploys the face recognition and face matching sub-service simultaneously, the server part deploys the face matching total service, the client uses the face recognition technology to extract the face information at the beginning, and uses the face information for the local face matching sub-service for matching, the matching is failed and then submitted to the total service of the server, after the matching is successful, the server returns the matching information to the client, the client localizes the matching information data, if the client recognizes the person again, only local self-matching is needed, thereby ensuring that the person who appears in the conference process or in the command scheduling process only needs to be matched by the server once, because the client locally supports the face recognition function, therefore, the head portrait of the person can be accurately found, the person information can be displayed in real time according to the head portrait position, the identification of hundreds of video pictures of the same conference is supported, and the concurrence of thousands of conferences by the server is also supported.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing descriptions of specific exemplary embodiments of the present invention have been presented for purposes of illustration and description. It is not intended to limit the invention to the precise form disclosed, and obviously many modifications and variations are possible in light of the above teaching. The exemplary embodiments were chosen and described in order to explain certain principles of the invention and its practical application to enable one skilled in the art to make and use various exemplary embodiments of the invention and various alternatives and modifications as are suited to the particular use contemplated. It is intended that the scope of the invention be defined by the claims and their equivalents.
Claims (10)
1. A face recognition method in a video conference process is characterized by comprising the following steps:
after a face recognition module of a local end of a client and a first face matching module of the local end are started, the face recognition module recognizes face information in a video stream of the client and records the positions of all faces, the display positions of personnel information corresponding to all face information are determined according to the positions of all faces, and the face information is extracted;
the first face matching module matches the face information extracted by the face recognition module with a first database prestored in the local end of the client; and
and if the first database stores the personnel information corresponding to the certain face information, the first face matching module judges that the face information is successfully matched and displays the personnel information corresponding to the face information at the display position of the personnel information.
2. The method of claim 1, wherein the face recognition method further comprises:
if the first database does not store the personnel information corresponding to the face information, the first face matching module judges that the face information fails to be matched;
the first face matching module sends face information failed in matching to a server;
the server starts a second face matching module of the server side;
a second face matching module of the server matches the face information of which the matching of the client fails with a second database prestored in the server;
if the second database stores the personnel information corresponding to the certain face information which fails to be matched with the client, the second face matching module judges that the face information is successfully matched, and the server sends the personnel information corresponding to the face information to the first face matching module of the client; and
and the first face matching module of the client displays the personnel information successfully matched by the server at the corresponding display position of the client according to the display position information of the personnel information determined by the face recognition module.
3. The method of face recognition during a video conference as claimed in claim 2, wherein said face recognition method further comprises:
and the first face matching module of the client stores the personnel information corresponding to the face information sent by the server to the first database of the local end.
4. The method of claim 1, wherein the face recognition method further comprises:
the first face matching module is used for regularly cleaning the personnel information in the first database according to the personnel information use frequency condition in the first database.
5. The method of claim 4, wherein the periodically cleaning the people information in the first database according to the people information usage frequency in the first database by the first face matching module comprises:
the first face matching module compares the number of personnel contained in the personnel information in the first database with a preset threshold value, and if the number of personnel is greater than the preset threshold value, the personnel information with low use frequency in the first database is cleaned, so that the number of personnel contained in the cleaned personnel information in the first database is not more than the preset threshold value.
6. The method of face recognition during a video conference as claimed in claim 2, wherein said face recognition method further comprises establishing said second database, wherein said establishing said second database comprises:
the server extracts the face information of the photo or the video input by the administrator or uploaded by the client, summarizes the face information and the corresponding personnel information and stores the summary into the second database.
7. A face recognition system during a video conference, comprising:
the first database is arranged at the client and used for storing the personnel information corresponding to the face information;
the face recognition module is arranged at the client and used for recognizing the face information in the video stream of the client, recording the position of each face, determining the display position of the personnel information corresponding to each face information according to the position of each face and extracting the face information; and
and the first face matching module is arranged at the client, is coupled with the first database and the face recognition module, and is used for matching the face information extracted by the face recognition module with a first database prestored at the local end of the client, judging that the face information is successfully matched if the first database stores the personnel information corresponding to the face information, and displaying the personnel information corresponding to the face information at the display position of the personnel information.
8. The system of claim 7, wherein the first face matching module is further configured to determine that the face information fails to be matched when the first database does not store the person information corresponding to the face information, and send the face information that fails to be matched to the server.
9. The system for face recognition during a video conference as claimed in claim 8, wherein said face recognition system further comprises:
the second database is arranged at the server end and used for storing the personnel information corresponding to the face information; and
the second face matching module is arranged at the server, is coupled with the first face matching module, the face recognition module and the second database, and is used for matching the face information failed in matching at the client with the second database prestored at the server; if the second database stores the personnel information corresponding to the certain face information which fails to be matched with the client, the matching of the face information is judged to be successful, and the personnel information corresponding to the face information is sent to the first face matching module;
the first face matching module is further used for displaying the personnel information successfully matched by the server at the corresponding display position of the client according to the display position information of the personnel information determined by the face recognition module.
10. A computer-readable storage medium for performing the face recognition method in a video conference according to any one of claims 1 to 6.
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| CN113129492A (en) * | 2021-04-16 | 2021-07-16 | 腾讯科技（深圳）有限公司 | Intelligent access control method and system |
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| CN113129492A (en) * | 2021-04-16 | 2021-07-16 | 腾讯科技（深圳）有限公司 | Intelligent access control method and system |
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