CN109359609B - Face recognition training sample acquisition method and device - Google Patents
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Abstract
The embodiment of the invention provides a method and a device for acquiring a face recognition training sample, and relates to the technical field of face recognition. The method and the device are used for acquiring a first face image associated with first biological identification information when the biological identification information matched with the acquired first biological identification information exists in a first biological identification information database, controlling an image acquisition device to acquire a second face image of a user, and determining the first face image and the second face image as face recognition training samples. Because the first face image and the second face image are associated by utilizing the first biological identification information, the face identification training sample can be reliably obtained under the condition of no manual participation, the efficiency and the accuracy are improved, and the labor cost can be saved: meanwhile, the problem that a snapshot human face sample is wrong due to personnel replacement during the period that the image acquisition equipment loses the shooting target is avoided by acquiring the second biological identification information associated with the first biological identification information.
Description
Technical Field
The invention relates to the technical field of face recognition, in particular to a method and a device for acquiring a face recognition training sample.
Background
Face recognition is a series of related technologies, which are generally called portrait recognition and facial recognition, that is, images or video streams containing faces are acquired by using a camera or a camera, the faces are automatically detected and tracked in the images, and then the detected faces are subjected to facial recognition. In the field of public safety, the research and application of the face recognition technology have very important practical significance. The face recognition technology comprises the steps of collecting face sample data, preprocessing a sample picture, training a model and recognizing the sample, wherein the collection of the sample data is the premise of face recognition.
In the prior art, a special sample collection worker is usually required to perform manual calibration according to differences such as light, angle, posture, shielding and the like, pictures meeting requirements are screened from massive picture data one by one, and then classified and put in storage and labeled, so that sample data is screened. However, because the number of the image data is huge, a large number of sample collection workers need to be invested, and the method is time-consuming, labor-consuming, slow in speed, low in efficiency and high in cost; meanwhile, errors exist in manual work, sample calibration is long-term repetitive work, and sample collection workers are difficult to avoid fatigue, so that final sample data errors are caused, and the trained face recognition system is unreliable.
Disclosure of Invention
In view of the above, the present invention provides a method and an apparatus for acquiring a face recognition training sample to solve the above problem.
In order to achieve the above purpose, the embodiment of the present invention adopts the following technical solutions:
in a first aspect, an embodiment of the present invention provides a method for obtaining a face recognition training sample, where the method for obtaining a face recognition training sample includes:
acquiring first biological identification information of a user;
when biometric information matched with the first biometric information exists in a pre-established first biometric information database, acquiring a pre-stored first face image associated with the first biometric information;
controlling an image acquisition device to acquire a second face image of the user;
and determining the first face image and the second face image as face recognition training samples.
In a second aspect, an embodiment of the present invention further provides a face recognition training sample acquiring apparatus, where the face recognition training sample acquiring apparatus includes:
a biometric information acquisition unit for acquiring first biometric information of a user;
the face image acquiring unit is used for acquiring a pre-stored first face image associated with first biological identification information when the biological identification information matched with the first biological identification information exists in a pre-established first biological identification information database;
the control unit is used for controlling an image acquisition device to acquire a second face image of the user;
and the face recognition training sample determining unit is used for determining the first face image and the second face image as face recognition training samples.
According to the method and the device for acquiring the face recognition training sample, the first biological recognition information of the user is acquired, when the biological recognition information matched with the first biological recognition information exists in the first biological recognition information database, the pre-stored first face image associated with the first biological recognition information is acquired, and meanwhile, an image acquisition device is controlled to acquire the second face image of the user, so that the first face image and the second face image are determined to be the face recognition training sample. The first face image and the second face image are associated by the first biological identification information, so that the face identification training sample can be reliably obtained under the condition of no manual participation, the efficiency and the accuracy are improved, and the labor cost is saved; meanwhile, the second biological identification information associated with the first biological identification information is acquired, and whether the target obtained again after the image acquisition equipment loses the target is a user with the first biological identification information is judged by taking the second biological identification information as a reference, so that the problem that a snapshot human face sample is wrong due to personnel replacement during the period that the image acquisition equipment loses the shooting target is avoided, and the reliability of the human face sample is ensured.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 shows a block schematic diagram of a server applicable to embodiments of the present invention.
Fig. 2 shows a flowchart of a method for acquiring a face recognition training sample according to an embodiment of the present invention.
Fig. 3 shows a functional block diagram of a face recognition training sample acquisition apparatus according to an embodiment of the present invention.
Icon: 100-a server; 111-a memory; 112-a processor; 113-a communication unit; 200-a face recognition training sample acquisition device; 210-a biometric information acquisition unit; 220-a judging unit; 230-a face image acquisition unit; 240-a control unit; 250-a face recognition training sample determination unit.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
It is noted that the relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Fig. 1 is a block diagram of a server 100. The server 100 includes a face recognition training sample acquisition device 200, a memory 111, a processor 112, and a communication unit 113.
The memory 111, the processor 112 and the communication unit 113 are electrically connected to each other directly or indirectly to realize data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The face recognition training sample acquiring device 200 includes at least one software functional module which can be stored in the memory 111 in the form of software or Firmware (Firmware) or solidified in an Operating System (OS) of the server 100. The processor 112 is used for executing executable modules stored in the memory 111, such as software functional modules and computer programs included in the face recognition training sample acquisition device 200.
The Memory 111 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like. The memory 111 is used to store programs or data. The communication unit 113 is configured to establish a communication connection between the server 100 and another communication terminal via the network, and to transceive data via the network.
It should be understood that the configuration shown in fig. 1 is merely a schematic diagram of the configuration of the server 100, and that the server 100 may include more or less components than those shown in fig. 1, or have a different configuration than that shown in fig. 1. The components shown in fig. 1 may be implemented in hardware, software, or a combination thereof.
First embodiment
The embodiment of the invention provides a method for acquiring a face recognition training sample, which is used for automatically acquiring the face recognition training sample on line without using manpower for distinguishing and calibrating. Fig. 2 is a flowchart of a method for acquiring a face recognition training sample according to an embodiment of the present invention. The method for acquiring the face recognition training sample comprises the following steps:
step S201: first biometric information of a user is acquired.
In an alternative embodiment, the first biometric information is fingerprint information. Correspondingly, the fingerprint information acquisition should be a fingerprint identification device. Accordingly, when the first biometric information is of another type, the corresponding acquisition device may be of another type.
Step S202: judging whether the pre-established first biological identification information database has biological identification information matched with the first biological identification information, if so, executing step S203; if not, step S201 is re-executed.
Wherein the pre-established first database of biometric information comprises biometric information of a plurality of users. Meanwhile, the memory 111 of the server 100 also stores face images of a large number of users, and each face image of a user is associated with biometric information of the user.
By determining whether or not there is biometric information matching the first biometric information in the pre-established first biometric information database, it is actually determined whether or not the face image of the user who owns the first biometric information is stored in the memory 111 of the server 100.
When the pre-established first biometric information database does not have biometric information matching the first biometric information, it indicates that the face image of the user is not stored in the memory 111 of the server 100, so that the face recognition training sample cannot be obtained, and the first biometric information needs to be obtained again for re-judgment.
In an alternative embodiment, the first biometric information is compared with all the biometric information contained in the first biometric information database one by one, and once the comparison is successful, a result that the biometric information matching the first biometric information exists in the pre-established first biometric information database can be obtained.
Further, it is understood that the first biometric information and the biometric information matching the first biometric information are the same user, the biometric information collected at present and the biometric information collected and stored in the past.
Step S203: and acquiring a pre-stored first face image associated with the first biological identification information.
When the pre-established first biological identification information database has biological identification information matched with the first biological identification information, the pre-stored first face image associated with the first biological identification information is directly acquired to form a face recognition training sample.
Step S204: and controlling an image acquisition device to acquire a second face image of the user.
Meanwhile, when the fact that the biological recognition information matched with the first biological recognition information exists in the pre-established first biological recognition information database is determined, an image acquisition device is controlled to acquire a second face image of the user to serve as another part of the face recognition training sample.
Step S205: and determining the first face image and the second face image as face recognition training samples.
It is to be understood that the face recognition training sample should contain at least two face images belonging to the same user. When the pre-established first biological recognition information database has biological recognition information matched with the first biological recognition information, the first face image associated with the first biological recognition information is used as one of the compared face images, and the second face image of the user is immediately collected to be used as the other face image, so that a complete face recognition training sample is formed.
Step S206: second biometric information associated with the first biometric information is acquired.
When the pre-established first biological identification information database has the biological identification information matched with the first biological identification information, the second biological identification information associated with the first biological identification information is acquired.
In this embodiment, the second biometric information is biometric information of the user who owns the first biometric information collected on site. And the second biometric information may be of the same type as the first biometric information or may be different. In an alternative embodiment, the second biometric information is voiceprint information. Voiceprint information is easier to collect relative to fingerprint information, a user does not need to actively put a hand into the fingerprint collecting device, and the voiceprint information can be collected by the voiceprint collecting device only by speaking. Of course, in other embodiments, the second biometric information may also be of other types, such as fingerprint information, iris information, and the like.
It should be noted that, in another alternative embodiment, the second biometric information database may also be stored in a second biometric information database that is established in advance, and the second biometric information database is searched and read directly according to the first biometric information without field collection.
In summary, the second biometric information is associated with both the first biometric information of the user himself and the first face image.
Step S207: judging whether an abnormal signal generated and sent by the image acquisition equipment is received, if so, performing step S208; if not, step S212 is performed.
It should be noted that, when the image capturing apparatus cannot capture the face image of the shooting target due to the shooting target turning around, being blocked, or other factors, an abnormal signal is generated and transmitted to the server 100.
When the abnormal signal generated and sent by the image acquisition device is not received, it indicates that the image acquisition device in the current state can acquire the third facial image of the user, so step S212 is executed at this time, and more training samples can be continuously acquired.
Step S208: and controlling the image acquisition equipment to stop shooting.
When the image capturing device generates an abnormal signal, it indicates that the image capturing device cannot capture a face image currently, so the server 100 controls the image capturing device to stop capturing, so as to avoid capturing too many unrelated images.
Step S209: judging whether a normal recovery signal generated and sent by the image acquisition equipment is received, if so, step S210; if not, the flow ends.
When a normal recovery signal generated and sent by the image acquisition equipment is received, the image acquisition equipment can shoot a face image of a shooting target at the moment, but whether the situation of personnel replacement exists during the period that the image acquisition equipment loses the shooting target cannot be determined, so that the subsequent process is required to further judge; and when a normal recovery signal generated and sent by the image acquisition equipment is not received, the face image cannot be further acquired, so that the process is directly ended.
Step S210: third biometric information of the user is obtained.
The third biological identification information is the biological identification information acquired by the image acquisition equipment in real time.
Step S211: judging whether the third biological identification information is matched with the second biological identification information, if so, executing step S212; if not, the flow ends.
It can be understood that, since the user may be in motion, but the position of the image capturing device is fixed, in the practical application, there is always a case where the image capturing device cannot capture the face image of the target user. Therefore, whether the third biological identification information is matched with the second biological identification information or not can be judged, whether the face picture which can be shot again after the image acquisition equipment loses the shooting target is the face picture which is shot before and has the user with the second biological identification information or not can be determined, the problem that the face sample which is shot is wrong due to personnel replacement during the period that the image acquisition equipment loses the shooting target is avoided, and the reliability of the face sample is guaranteed.
When the third biological identification information is not matched with the second biological identification information, the fact that personnel replacement occurs during the period that the image acquisition equipment loses the shooting target is indicated, and the training sample can not be obtained any more, so that the process is directly finished.
Step S212: and controlling the image acquisition equipment to acquire a third face image of the user again.
When the third biological identification information is matched with the second biological identification information, the shooting target of the image acquisition equipment is not changed, namely the user with the first biological identification information and the second biological identification information is obtained, and at the moment, the third face image is acquired again to serve as a new face identification training sample.
Step S213: and determining the third face image and the first face image as face recognition training samples.
Specifically, a discussion is developed by taking a remote assistant and education meeting scene of a police law as an example, and an application process of the method for acquiring the face recognition training sample provided by the invention is described in detail.
The method comprises the steps of firstly collecting first biological identification information, namely fingerprint information, at an entrance, inquiring whether the fingerprint information exists in a pre-established fingerprint database, if so, controlling a camera at the entrance to carry out face snapshot to obtain a second face image, and simultaneously obtaining a certificate photo of a user, namely a first face image, and sending the second face image which is in parallel connection with the camera at the entrance and is taken as a face identification training sample to a face identification training subsystem for model training.
After entering the meeting room, the continuous collection of the voiceprint is started, and the first collected second biological identification information, namely the voiceprint information is stored in the database to be used as the base line of the subsequent voiceprint identification. Then special attention is paid to the abnormal condition that the human face cannot be captured by the camera: once the face leaves the capturing area of the camera, for example, the camera is twisted or moved, the camera cannot capture the face normally. When the abnormal condition is recovered, the face snapshot function of the camera needs to be suspended. And comparing the collected voiceprints with voiceprint data recorded in the database for the first time, starting the normal face snapshot of the camera by the system to acquire a third face image only after the voiceprints are successfully compared, and connecting the third face image and the first face image together as a face recognition training sample to a face recognition training subsystem for model training.
Second embodiment
Referring to fig. 3, fig. 3 is a functional block diagram of a face recognition training sample acquiring apparatus 200 according to a preferred embodiment of the present invention. It should be noted that the basic principle and the generated technical effect of the face recognition training sample acquiring device 200 provided in the present embodiment are the same as those of the above embodiments, and for the sake of brief description, no part of the present embodiment is mentioned, and reference may be made to the corresponding contents in the above embodiments. The face recognition training sample acquisition apparatus 200 includes a biometric information acquisition unit 210, a determination unit 220, a face image acquisition unit 230, a control unit 240, and a face recognition training sample determination unit 250.
The biometric information acquiring unit 210 is configured to acquire first biometric information of a user.
It is to be understood that, in a preferred embodiment, the biometric information acquisition unit 210 is operable to execute step S201.
The judging unit 220 is configured to judge whether there is biometric information matching the first biometric information in the pre-established first biometric information database.
It is to be understood that, in a preferred embodiment, the determining unit 220 is operable to execute the step S202.
The facial image acquiring unit 230 is configured to acquire a pre-stored first facial image associated with first biometric information when biometric information matching the first biometric information exists in a pre-established first biometric information database.
It is to be understood that, in a preferred embodiment, the face image obtaining unit 230 is operable to execute step S203.
The control unit 240 is configured to control an image capturing device to capture a second facial image of the user.
It is to be understood that, in a preferred embodiment, the control unit 240 is operable to execute step S204.
The face recognition training sample determination unit 250 is configured to determine the first face image and the second face image as face recognition training samples.
It is to be understood that, in a preferred embodiment, the face recognition training sample determination unit 250 is operable to execute step S205.
The biometric information acquisition unit 210 is also configured to acquire second biometric information associated with the first biometric information.
It is to be understood that, in a preferred embodiment, the biometric information acquisition unit 210 is operable to perform step S206.
The determining unit 220 is further configured to determine whether an abnormal signal generated and sent by the image capturing device is received.
It is to be understood that, in a preferred embodiment, the determining unit 220 can be used for executing the step S207.
The control unit 240 is further configured to control the image capturing apparatus to stop shooting when an abnormal signal generated and transmitted by the image capturing apparatus is not received.
It is to be understood that, in a preferred embodiment, the control unit 240 is operable to execute step S208.
The determining unit 220 is further configured to determine whether a normal recovery signal generated and sent by the image capturing device is received.
It is to be understood that, in a preferred embodiment, the judging unit 220 is operable to execute the step S209.
The biometric information acquisition unit 210 is further configured to acquire third biometric information of the user when receiving a normal return signal generated and transmitted by the image capturing apparatus.
It is to be understood that, in a preferred embodiment, the biometric information acquisition unit 210 is operable to perform step S210.
The determination unit 220 is further configured to determine whether the third biometric information matches the second biometric information.
It is to be understood that, in a preferred embodiment, the judging unit 220 can be used for executing the step S211.
The control unit 240 is further configured to control the image capturing device to re-capture the third face image of the user when the third biometric information matches the second biometric information.
It is to be understood that, in a preferred embodiment, the control unit 240 is operable to execute step S212.
The face recognition training sample determination unit 250 is further configured to determine the third face image and the first face image as the face recognition training samples.
It is to be understood that in a preferred embodiment, the face recognition training sample determination unit 250 is operable to perform step S213.
In summary, according to the method and apparatus for acquiring a face recognition training sample provided by the embodiments of the present invention, by acquiring first biometric information of a user, when biometric information matching the first biometric information exists in a first biometric information database, a pre-stored first face image associated with the first biometric information is acquired, and an image acquisition device is controlled to acquire a second face image of the user, so that the first face image and the second face image are determined as a face recognition training sample. The first face image and the second face image are associated by the first biological identification information, so that the face identification training sample can be reliably obtained under the condition of no manual participation, the efficiency and the accuracy are improved, and the labor cost is saved.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some implementations, where identified as alternative, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and identified as separate product sales or use, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (2)
1. A face recognition training sample acquisition method is characterized by comprising the following steps:
acquiring first biological identification information of a user, wherein the first biological identification information is fingerprint information;
when the first biological identification information database which is pre-established has biological identification information which is matched with the first biological identification information, acquiring a pre-stored first face image which is associated with the first biological identification information;
controlling an image acquisition device to acquire a second face image of the user;
determining the first face image and the second face image as face recognition training samples;
acquiring second biological identification information associated with the first biological identification information, wherein the second biological identification information is voiceprint information;
when an abnormal signal generated and sent by the image acquisition equipment is received, controlling the image acquisition equipment to stop shooting;
when a normal recovery signal generated and sent by the image acquisition equipment is received, acquiring third biological identification information of the user; wherein the third biological identification information is voiceprint information;
when the third biological identification information is matched with the second biological identification information, controlling the image acquisition equipment to acquire a third face image of the user again;
and determining the third face image and the first face image as face recognition training samples.
2. A face recognition training sample acquisition device, characterized by comprising:
the biometric information acquisition unit is used for acquiring first biometric information of a user, wherein the first biometric information is fingerprint information;
the face image acquiring unit is used for acquiring a pre-stored first face image associated with first biological identification information when the biological identification information matched with the first biological identification information exists in a pre-established first biological identification information database;
the control unit is used for controlling an image acquisition device to acquire a second face image of the user;
a face recognition training sample determination unit, configured to determine the first face image and the second face image as face recognition training samples;
the biometric information acquisition unit is further used for acquiring second biometric information associated with the first biometric information, wherein the second biometric information is voiceprint information;
the control unit is also used for controlling the image acquisition equipment to stop shooting when receiving an abnormal signal generated and sent by the image acquisition equipment;
the biometric information acquisition unit is further used for acquiring third biometric information of the user when a normal recovery signal generated and sent by the image acquisition equipment is received; wherein the third biological identification information is voiceprint information;
the face image acquisition unit is further used for controlling the image acquisition equipment to acquire a third face image of the user again when the third biological identification information is matched with the second biological identification information;
the face recognition training sample determining unit is further configured to determine the third face image and the first face image as face recognition training samples.
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| CN110503150A (en) * | 2019-08-26 | 2019-11-26 | 苏州科达科技股份有限公司 | Sample data acquisition method, device and storage medium |
| CN111046806A (en) * | 2019-12-12 | 2020-04-21 | 天地伟业技术有限公司 | Heterogeneous image face recognition target library generation method |
| CN112529128A (en) * | 2021-02-09 | 2021-03-19 | 北京声智科技有限公司 | Biological sample collection method and device, computer equipment and storage medium |
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