WO2020006727A1 - Face recognition method and device, and server - Google Patents

Face recognition method and device, and server Download PDF

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Publication number
WO2020006727A1
WO2020006727A1 PCT/CN2018/094628 CN2018094628W WO2020006727A1 WO 2020006727 A1 WO2020006727 A1 WO 2020006727A1 CN 2018094628 W CN2018094628 W CN 2018094628W WO 2020006727 A1 WO2020006727 A1 WO 2020006727A1
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WIPO (PCT)
Prior art keywords
user
preset
information
comparison range
base station
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PCT/CN2018/094628
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French (fr)
Chinese (zh)
Inventor
张站朝
廉士国
黄晓庆
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深圳前海达闼云端智能科技有限公司
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Priority to PCT/CN2018/094628 priority Critical patent/WO2020006727A1/en
Priority to CN201880001396.8A priority patent/CN108885698B/en
Publication of WO2020006727A1 publication Critical patent/WO2020006727A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • 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
    • G06V40/168—Feature extraction; Face representation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • 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
    • G06V40/172—Classification, e.g. identification

Definitions

  • the embodiments of the present application relate to the field of face recognition technology, for example, to a face recognition method, device, and server.
  • Face recognition technology is currently widely used in the field of artificial intelligence vision. Face recognition technology obtains images of users whose identity is to be determined through image acquisition equipment, then detects the face image in the image, and then uses the algorithm to face the image. Feature extraction is performed, and then the extracted features are compared with the existing templates in the preset face feature database to find similarity faces as the recognition result to determine the identity of the user.
  • the related technology has at least the following problems:
  • the number of face features included in the preset face feature database is large,
  • the range of feature comparison is large, and the accuracy of recognition may decrease. Therefore, it is necessary to provide a face recognition method that can reduce the comparison range of face features and improve the accuracy of recognition.
  • An object of the embodiments of the present application is to provide a face recognition method, device, and server that can reduce the comparison range of face features and improve the recognition accuracy rate.
  • an embodiment of the present application provides a face recognition method.
  • the face recognition method is applied to a server, and the method includes:
  • both of the preset facial feature database and the facial feature comparison range include known users Facial feature and user information, the facial feature comparison range includes fewer faces than the number of faces included in the preset face feature database;
  • Identify the face feature based on the face feature comparison range and instruct the robot to query the user to be identified according to the recognition result.
  • an embodiment of the present application further provides a face recognition device.
  • the face recognition device is applied to a server, and the device includes:
  • a face feature acquisition module configured to obtain a face image of a user whose identity is to be determined, and obtain a face feature of the face image based on the recognition of the face image;
  • a facial feature comparison range acquisition module is configured to obtain positioning information of a positioning device, and obtain a facial feature comparison range from a preset face feature database based on the positioning information, the preset face feature database and the The facial feature comparison range includes facial features and user information of a known user, and the facial feature comparison range includes fewer faces than the number of faces included in the preset face feature database;
  • a recognition module configured to recognize the facial feature based on the facial feature comparison range, and instruct the robot to query the user to be identified according to the recognition result.
  • an embodiment of the present application further provides a server, including:
  • At least one processor At least one processor
  • a memory connected in communication with the at least one processor; wherein,
  • the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can execute the foregoing method.
  • the face recognition method, device, and server provided in the embodiments of the present application obtain the positioning information of a positioning device, and obtain a facial feature comparison range from a preset facial feature database according to the positioning information, and identify a user to be identified.
  • the facial features of are identified based on the facial feature comparison range to identify the identity of the user whose identity is to be determined. Because the narrowed face feature comparison range is used compared to the preset face feature database, the recognition accuracy rate is improved.
  • FIG. 1 is a schematic diagram of an application scenario of the applicant's face recognition method and device
  • FIG. 2 is a flowchart of an embodiment of the applicant's face recognition method
  • FIG. 3 is a flowchart of an embodiment of the applicant's face recognition method
  • FIG. 4 is a schematic structural diagram of an embodiment of the applicant's face recognition device
  • FIG. 5 is a schematic structural diagram of an embodiment of the applicant's face recognition device
  • FIG. 6 is a schematic diagram of a hardware structure of a server according to an embodiment of the present application.
  • the face recognition method and device provided in the embodiments of the present application are applicable to the application scenario shown in FIG. 1.
  • the application scenario shown in FIG. 1 includes a face recognition system 100 and a cloud server 200.
  • the face recognition system 100 includes a server 10, an image acquisition device 20, at least one positioning device 30, and a robot 40.
  • the cloud server 200 is loaded with a preset facial feature database, which includes the facial features of known users and user information (such as a user identity).
  • the image acquisition device 20 is configured to acquire an image of a user and send the image to the server 10.
  • the positioning device 30 is configured to locate a related user, and obtain user information of the related user and send it to the server 10.
  • the server 10 reduces the preset facial feature database according to the information sent by the positioning device 30 to obtain a facial feature comparison range that includes only the facial features of the relevant user.
  • the server 10 identifies the face image in the image of the identified user, and uses an algorithm to perform face feature extraction on the face image of the identified user (for example, based on a pre-trained neural network model, extracts face features from the face image) ), And then comparing and identifying the facial features based on the facial feature comparison range to confirm the identity of the user to be identified.
  • the use of narrowed facial feature comparison range to compare and recognize the facial features of the identified users can improve the accuracy of recognition.
  • the image acquisition device 20 may be a camera, a video camera, a camera, a scanner, or other devices (smartphones, tablets, etc.) with a photographing function.
  • the positioning device 30 is, for example, a base station, a WIFI positioning device, or the like.
  • the robot 40 may be a fixed-position robot or a movable robot. Face recognition algorithms are, for example, recognition algorithms based on facial feature points, recognition algorithms based on entire face images, recognition algorithms based on templates, and recognition algorithms based on neural networks.
  • the cloud server 200 may not be used, and the preset face feature database may be loaded into the server 10 of the local face recognition system 100.
  • the image acquisition device 20 may be provided separately (for example, at the door of a room), or may be integrated on the robot 40.
  • the number of the server 10, the image acquisition device 20, the positioning device 30, and the robot 40 may be one or more.
  • FIG. 2 is a flowchart of an embodiment of a face recognition method according to an embodiment of the present application.
  • the face recognition method may be executed by the server 10 in FIG. 1. As shown in FIG. 1
  • the image of the to-be-identified user may be collected by the image acquisition device 20.
  • the server 10 After receiving the image of the to-be-identified user, the server 10 recognizes the face image in the image and uses an algorithm to perform a face treatment on the face image of the to-be-identified user Feature extraction, for example, extracting face features from a face image based on a pre-trained neural network model.
  • Obtain positioning information of a positioning device and obtain a facial feature comparison range from a preset facial feature database based on the positioning information.
  • the preset facial feature database and the facial feature comparison range both include Knowing the user's face features and user information, the number of faces included in the face feature comparison range is less than the number of faces included in the preset face feature database.
  • the positioning device 30 locates the relevant user, and obtains the positioning information and sends it to the server 10, where the positioning information includes the user's information (such as the user's identity).
  • the server 10 reduces the preset facial feature database according to the information of the related user, and obtains a facial feature comparison range including only the facial features of the related user.
  • the positioning device 30 may include a first base station and a second base station, and the facial feature comparison range includes a first facial feature comparison range and a second facial feature comparison range.
  • the server 10 obtains a first face feature comparison range from a preset face feature database by using the positioning information located by the first base station, and obtains a second face from the preset face feature database by using the information located by the second base station.
  • Feature comparison range Specifically, the first base station and the second base station can locate the position of the user by locating an electronic device such as a mobile phone carried by the user, so as to obtain related users who appear in a certain area.
  • the face recognition method in the embodiment of the present application can be applied to a variety of face recognition scenarios, including various business halls (such as telecommunication business halls, ticket sales halls, or other business halls), railway stations, and airports.
  • the first base station may be a base station installed indoors
  • the second base station may be a base station installed outdoors.
  • the first base station locates a user in the room at the current time (for example, the current time or the current time), and sends the user's information (for example, the user's identity) to the server 10, and the server 10 uses the preset face characteristics Find the facial features of indoor users in the database as the first facial feature comparison range.
  • the purpose of setting the second base station is to find the person who is most likely to handle the business indoors.
  • the positioning method of the second base station can be adjusted according to the specific application scenario.
  • the second base station may locate and obtain information of a user appearing in a preset area within the first preset period, and send the information to the server 10.
  • the first preset time period and the preset area can be set in advance.
  • the first preset time period is, for example, one year, half a year, one month, or other time.
  • the preset area can be a certain area near the indoor area, such as the indoor area.
  • the information sent by the second base station to the server 10 may include the user's identity, appearance time, and so on.
  • the user's identity can be a unique identifier that the SIM card uses to mark the user's identity, such as a mobile phone number.
  • the server 10 determines, based on the positioning information of the second base station, users (such as 20 days in one month or two months in half a year) that appear more frequently in the area, and obtains The information of these users is the first user information.
  • the server 10 acquires users who have handled the business indoors within a second preset period (for example, one month), and obtains the information of these users as the second user information.
  • the server 10 obtains the third user information by intersecting the first user information and the second user information, and obtains the second facial feature comparison range according to the third user information.
  • the first face feature comparison range and the second face feature comparison range may be a data sub-database obtained by the server 10 from a preset face feature library, or may still exist in the preset person.
  • the facial feature database only labels are used to distinguish them from other data in the preset facial feature database.
  • the positioning device 30 may include only one type of base station, for example, a base station installed indoors or a base station installed in a certain area outdoors.
  • the server 10 obtains only one face feature comparison range from a preset face feature database according to the positioning information of the base station.
  • the facial feature comparison range may also include more comparison ranges, such as the first face feature comparison range, the second face feature comparison range, and the third face feature comparison. The scope and the like are not limited in the embodiments of the present application.
  • 103 Identify the facial features based on the facial feature comparison range, and instruct the robot to inquire about the identified user according to the recognition result.
  • the first facial feature comparison range is set to include the facial features of indoor users. Reduce the range of facial feature comparison. As long as the user is located by the first base station when entering the room, his face features can enter the first face feature comparison range, and the server 10 can quickly and accurately identify the to-be-determined based on the first face feature comparison range. Identity user. If the primary recognition result of the first facial feature comparison range comparison has facial features with a similarity greater than or equal to a first preset threshold, it is confirmed that the identity of the user corresponds to the facial feature with the highest similarity. The user does not need to compare the facial feature comparison range with the second facial feature comparison.
  • the server 10 may then compare the user's face features with the second face feature comparison range. If there are face features with similarity greater than or equal to the first preset threshold in the recognition result, then confirm the user ’s The identity is the user corresponding to the face feature with the highest similarity.
  • the robot 40 is instructed to determine The identity user asks if he is one of the users with the highest similarity.
  • the questioning manner can be presented in a manner of selecting a question.
  • the identities of the users with the highest similarity obtained by the server 10 are Li XX, Zhang XX, and Wang XX, respectively.
  • the robot 40 may ask the user to be identified, "Are you Mr. Li, Mr. Zhang, or Mr. Wang?"
  • the identity of the user to be identified can be determined by an affirmative or negative answer of the user to be identified.
  • This selective inquiry method can give users a sense of intimacy and improve the user experience.
  • the robot 40 sends the answer result of the user to be identified to the server 10, the server 10 According to the answer result of the to-be-identified user, extract the facial features of the to-be-identified user, and upload the to-be-identified user ’s face features, user identity information, and photos to a preset face feature database to improve the next time. Recognition accuracy.
  • the server 10 may directly instruct the robot 40 to query the user information of the user whose identity is to be determined, and then according to the user ’s The information searches the preset facial feature database for the corresponding facial feature of the user, and compares the obtained facial feature with the facial feature of the user to determine the identity of the user.
  • the facial feature comparison range includes only one facial feature comparison range
  • the recognition result obtained through the facial feature comparison range includes facial features with a degree of similarity greater than or equal to a first preset threshold
  • the recognition result obtained through the facial feature comparison range includes facial features with a degree of similarity greater than or equal to a first preset threshold
  • the maximum similarity in the recognition result is greater than the second preset threshold value and less than the first preset threshold value
  • users corresponding to the facial features in the first few (such as the first three) similarities can be obtained, and then the robot 40 is instructed to determine
  • the identity user asks if he is one of the users with the highest similarity.
  • the server 10 may directly instruct the robot 40 to query user information of the user whose identity is to be determined.
  • the first preset threshold and the second preset threshold can be set in advance.
  • the first preset threshold is set to 60%
  • the second preset threshold is set to 55%.
  • the facial features of a user to be identified are based on the facial feature ratio. Compare and identify the range to identify the identity of the user to be identified. Because the narrowed face feature comparison range compared to the preset face feature database is used, the recognition accuracy is improved, and the recognition speed is also provided.
  • an embodiment of the present application further provides a face recognition device.
  • the face recognition device is used in the server 10 shown in FIG. 1.
  • the face recognition device 400 includes:
  • a face feature obtaining module 401 configured to obtain a face image of a user whose identity is to be determined, and obtain a face feature of the face image by performing recognition based on the face image;
  • a facial feature comparison range acquisition module 402 is configured to acquire positioning information of a positioning device, and obtain a facial feature comparison range from a preset face feature database based on the positioning information, the preset face feature database and
  • the face feature comparison range includes the face features and user information of a known user, and the face feature comparison range includes fewer faces than the number of faces included in the preset face feature database;
  • the recognition module 403 is configured to recognize the facial features based on the facial feature comparison range, and instruct the robot to query the user to be identified according to the recognition result.
  • the facial features of a user to be identified are based on the facial feature ratio. Compare and identify the range to identify the identity of the user to be identified. Because the narrowed face feature comparison range compared to the preset face feature database is used, the recognition accuracy is improved, and the recognition speed is also provided.
  • the recognition module 403 is specifically configured to:
  • the robot is instructed to make an inquiry based on the user identity information corresponding to the at least one face feature.
  • the identification module 403 is specifically configured to:
  • the robot is instructed to query the user identity information of the user whose identity is to be determined.
  • the positioning device includes a first base station and a second base station, and the face feature comparison range includes a first face feature comparison range and a second Facial feature comparison range;
  • the facial feature comparison range acquisition module 402 includes:
  • a first facial feature comparison range acquisition submodule 4021 is configured to acquire positioning information of the first base station, and obtain a first facial feature comparison from a preset facial feature database based on the positioning information of the first base station. range;
  • a second facial feature comparison range acquisition submodule 4022 is configured to acquire positioning information of the second base station, and obtain a second facial feature comparison from a preset facial feature database based on the positioning information of the second base station. range;
  • the identification module 403 is further specifically configured to:
  • the facial features are identified based on the second facial feature comparison range to obtain a recognition result.
  • the first base station is an indoor base station, and the second base station is an outdoor base station;
  • the first facial feature comparison range acquisition sub-module 4021 is specifically configured to:
  • the second facial feature comparison range acquisition sub-module 4022 is specifically configured to:
  • the positioning information of the second base station includes information of a user appearing in a preset area within a first preset period, and obtaining the first according to the positioning information of the second base station User information, where the first user information is information of a user who appears in the preset area for a first preset period of time and exceeds a preset time threshold;
  • the second user information is information of a user who has visited the room within a second preset period
  • the face recognition device 400 further includes:
  • the uploading module 404 is configured to receive a user confirmation message sent by the robot, and upload, according to the user confirmation message, the facial features, user identity information, and images of the user whose identity is to be determined to the preset facial feature database.
  • the above-mentioned face recognition device can execute the face recognition method provided in the embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method.
  • the face recognition method provided in the embodiment of the present application.
  • FIG. 6 is a schematic diagram of a hardware structure of a server 10 according to an embodiment of the present application. As shown in FIG. 6, the server 10 includes:
  • One processor 11 is taken as an example in FIG. 6.
  • the processor 11 and the memory 12 may be connected through a bus or in other manners.
  • the connection through the bus is taken as an example.
  • the memory 12 is a non-volatile computer-readable storage medium and can be used to store non-volatile software programs, non-volatile computer executable programs, and modules, such as programs corresponding to the face recognition method in the embodiments of the present application. Instructions / modules (for example, the facial feature acquisition module 401, the facial feature comparison range acquisition module 402, and the recognition module 403 shown in FIG. 4).
  • the processor 11 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions, and modules stored in the memory 12, that is, the face recognition method of the above method embodiment is implemented.
  • the memory 12 may include a storage program area and a storage data area, wherein the storage program area may store an operating system and an application program required for at least one function; the storage data area may store data created according to the use of the face recognition device and the like.
  • the memory 12 may include a high-speed random access memory, and may further include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage device.
  • the memory 12 may optionally include a memory remotely disposed with respect to the processor 11, and these remote memories may be connected to the face recognition device through a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.
  • the one or more modules are stored in the memory 12, and when executed by the one or more processors 11, execute the face recognition method in any of the above method embodiments, for example, execute FIG. 2 described above.
  • the method includes steps 101 to 103 in the method, steps 201 to 205 in the method in FIG. 3, and implements the functions of modules 401-430 in FIG. 4, modules 401-404 in FIG.
  • the above product can execute the method provided in the embodiment of the present application, and has corresponding function modules and beneficial effects of executing the method.
  • the above product can execute the method provided in the embodiment of the present application, and has corresponding function modules and beneficial effects of executing the method.
  • An embodiment of the present application provides a non-volatile computer-readable storage medium.
  • the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are executed by one or more processors, for example, as shown in FIG. 7.
  • a processor 11 may enable the one or more processors to execute the face recognition method in any of the foregoing method embodiments, for example, to execute the method steps 101 to 103 in FIG. 2 described above, and the steps in FIG. 3 Steps 201 to 205 of the method; the functions of modules 401-403 in FIG. 4, modules 401-404 in FIG. 5, and sub-modules 4021-4022 are implemented.
  • the device embodiments described above are only schematic, and the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located One place, or it can be distributed across multiple network elements. Some or all of the modules may be selected according to actual needs to achieve the objective of the solution of this embodiment.
  • the embodiments can be implemented by means of software plus a general hardware platform, and of course, they can also be implemented by hardware.
  • a person of ordinary skill in the art can understand that all or part of the processes in the method of the foregoing embodiment can be completed by using a computer program to instruct related hardware.
  • the program can be stored in a computer-readable storage medium. When executed, the processes of the embodiments of the methods described above may be included.
  • the storage medium may be a magnetic disk, an optical disk, a read-only memory (Read-Only Memory, ROM), or a random access memory (Random Access Memory, RAM).

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Abstract

Embodiments of the present application relate to a face recognition method and device, and a server. The method comprises: obtaining a face image of a user, and recognizing, on the basis of the face image, face features of the obtained face image; obtaining positioning information of a positioning device, and obtaining a face feature comparison range from a preset face feature library on the basis of the positioning information, the preset face feature library and the face feature comparison range comprising the face features and user information of the known user, and the number of faces comprised in the face feature comparison range being less than that of the faces comprised in the preset face feature library; and recognizing the face features on the basis of the face feature comparison range, and instructing, according to the recognition result, a robot to inquire the user whose identity is to be determined. The embodiments of the present application use the face feature comparison range which is narrowed with respect to the preset face feature library, and improves the recognition accuracy.

Description

人脸识别方法、装置和服务器Face recognition method, device and server 技术领域Technical field
本申请实施例涉及人脸识别技术领域，例如涉及一种人脸识别方法、装置和服务器。The embodiments of the present application relate to the field of face recognition technology, for example, to a face recognition method, device, and server.
背景技术Background technique
人脸识别技术目前在人工智能视觉领域中得到了广泛应用，人脸识别技术通过图像采集设备获取待确定身份用户的图像，然后在所述图像中检测人脸图像，再利用算法对人脸图像进行特征提取，进而将提取的特征与预设人脸特征库中已有的范本进行相似性比对，找出相似度最高的人脸作为识别结果，以判断用户的身份。Face recognition technology is currently widely used in the field of artificial intelligence vision. Face recognition technology obtains images of users whose identity is to be determined through image acquisition equipment, then detects the face image in the image, and then uses the algorithm to face the image. Feature extraction is performed, and then the extracted features are compared with the existing templates in the preset face feature database to find similarity faces as the recognition result to determine the identity of the user.
在研究现有技术的过程中，发明人发现相关技术中至少存在如下问题：在自然场景下进行人脸识别时，在预设人脸特征库包含的人脸特征数量较大时，由于人脸特征比对范围较大，可能会出现识别正确率下降的情况。因此，有必要提供一种能缩小人脸特征比对范围，提高识别正确率的人脸识别方法。In the process of studying the prior art, the inventors found that the related technology has at least the following problems: When performing face recognition in natural scenes, when the number of face features included in the preset face feature database is large, The range of feature comparison is large, and the accuracy of recognition may decrease. Therefore, it is necessary to provide a face recognition method that can reduce the comparison range of face features and improve the accuracy of recognition.
发明内容Summary of the invention
本申请实施例的一个目的是提供一种能缩小人脸特征比对范围，提高识别正确率的人脸识别方法、装置和服务器。An object of the embodiments of the present application is to provide a face recognition method, device, and server that can reduce the comparison range of face features and improve the recognition accuracy rate.
第一方面，本申请实施例提供了一种人脸识别方法，所述人脸识别方法应用于服务器，所述方法包括：In a first aspect, an embodiment of the present application provides a face recognition method. The face recognition method is applied to a server, and the method includes:
获取待确定身份用户的人脸图像，基于所述人脸图像进行识别获得所述人脸图像的人脸特征；Obtaining a face image of a user whose identity is to be determined, and identifying based on the face image to obtain a face feature of the face image;
获取定位装置的定位信息，基于所述定位信息从预设人脸特征库中获得人脸特征比对范围，所述预设人脸特征库和所述人脸特征比对范围均包括已知用户的人脸特征和用户信息，所述人脸特征比对范围包括的人脸数量小于所述预设人脸特征库中包括的人脸数量；Acquire positioning information of a positioning device, and obtain a facial feature comparison range from a preset facial feature database based on the positioning information, both of the preset facial feature database and the facial feature comparison range include known users Facial feature and user information, the facial feature comparison range includes fewer faces than the number of faces included in the preset face feature database;
将所述人脸特征基于所述人脸特征比对范围进行识别，并根据识别结果指示机器人对所述待确定身份用户进行询问。Identify the face feature based on the face feature comparison range, and instruct the robot to query the user to be identified according to the recognition result.
第二方面，本申请实施例还提供了一种人脸识别装置，所述人脸识别装置应用于服务器，所述装置包括：In a second aspect, an embodiment of the present application further provides a face recognition device. The face recognition device is applied to a server, and the device includes:
人脸特征获取模块，用于获取待确定身份用户的人脸图像，基于所述人脸图像进行识别获得所述人脸图像的人脸特征；A face feature acquisition module, configured to obtain a face image of a user whose identity is to be determined, and obtain a face feature of the face image based on the recognition of the face image;
人脸特征比对范围获取模块，用于获取定位装置的定位信息，基于所述定位信息从预设人脸特征库中获得人脸特征比对范围，所述预设人脸特征库和所述人脸特征比对范围均包括已知用户的人脸特征和用户信息，所述人脸特征比对范围包括的人脸数量小于所述预设人脸特征库中包括的人脸数量；A facial feature comparison range acquisition module is configured to obtain positioning information of a positioning device, and obtain a facial feature comparison range from a preset face feature database based on the positioning information, the preset face feature database and the The facial feature comparison range includes facial features and user information of a known user, and the facial feature comparison range includes fewer faces than the number of faces included in the preset face feature database;
识别模块，用于将所述人脸特征基于所述人脸特征比对范围进行识别，并根据识别结果指示机器人对所述待确定身份用户进行询问。A recognition module, configured to recognize the facial feature based on the facial feature comparison range, and instruct the robot to query the user to be identified according to the recognition result.
第三方面，本申请实施例还提供了一种服务器，包括：In a third aspect, an embodiment of the present application further provides a server, including:
至少一个处理器；以及，At least one processor; and
与所述至少一个处理器通信连接的存储器；其中，A memory connected in communication with the at least one processor; wherein,
所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行上述的方法。The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can execute the foregoing method.
本申请实施例提供的人脸识别方法、装置和服务器，通过获取定位装置的定位信息，并根据所述定位信息从预设人脸特征库中获得人脸特征比对范围，将待确定身份用户的人脸特征基于所述人脸特征比对范围进行识别以识别待确定身份用户的身份。因为采用了相对于预设人脸特征库缩小的人脸特征比对范围，提高了识别正确率。The face recognition method, device, and server provided in the embodiments of the present application obtain the positioning information of a positioning device, and obtain a facial feature comparison range from a preset facial feature database according to the positioning information, and identify a user to be identified. The facial features of are identified based on the facial feature comparison range to identify the identity of the user whose identity is to be determined. Because the narrowed face feature comparison range is used compared to the preset face feature database, the recognition accuracy rate is improved.
附图说明BRIEF DESCRIPTION OF THE DRAWINGS
一个或多个实施例通过与之对应的附图中的图片进行示例性说明，这些示例性说明并不构成对实施例的限定，附图中具有相同参考数字标号的元件表示为类似的元件，除非有特别申明，附图中的图不构成比例限制。One or more embodiments are exemplified by the pictures in the accompanying drawings. These exemplary descriptions do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the drawings in the drawings do not constitute a limitation on scale.
图1是本申请人脸识别方法和装置的应用场景示意图；FIG. 1 is a schematic diagram of an application scenario of the applicant's face recognition method and device;
图2是本申请人脸识别方法的一个实施例的流程图；2 is a flowchart of an embodiment of the applicant's face recognition method;
图3是本申请人脸识别方法的一个实施例的流程图；3 is a flowchart of an embodiment of the applicant's face recognition method;
图4是本申请人脸识别装置的一个实施例的结构示意图；4 is a schematic structural diagram of an embodiment of the applicant's face recognition device;
图5是本申请人脸识别装置的一个实施例的结构示意图；5 is a schematic structural diagram of an embodiment of the applicant's face recognition device;
图6是本申请实施例提供的服务器的硬件结构示意图。FIG. 6 is a schematic diagram of a hardware structure of a server according to an embodiment of the present application.
具体实施方式detailed description
为使本申请实施例的目的、技术方案和优点更加清楚，下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。In order to make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments These are part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in this application, all other embodiments obtained by a person of ordinary skill in the art without creative efforts shall fall within the protection scope of this application.
本申请实施例提供的人脸识别方法和装置，适用于图1所示的应用场景。在图1所示的应用场景中，包括人脸识别***100和云端服务器200。其中，人脸识别***100包括服务器10、图像采集装置20、至少一个定位装置30和机器人40。云端服务器200装载有预设人脸特征库，所述预设人脸特征库包括已知用户的人脸特征和用户信息(例如用户身份标识)。图像采集装置20用于采集用户的图像，并将所述图像发送给服务器10。定位装置30用于定位相关用户，并获得相关用户的用户信息发送给服务器10。服务器10根据定位装置30发送的信息对预设人脸特征库进行缩小，获得只包括相关用户的人脸特征的人脸特征比对范围。服务器10识别待确定身份用户的图像中的人脸图像，并利用算法对待确定身份用户的人脸图像进行人脸特征提取(例如基于预先训练好的神经网络模型对人脸图像进行人脸特征提取)，然后将人脸特征基于所述人脸特征比对范围进行比对识别，以确认待确定身份用户的身份。采用缩小的人脸特征比对范围对待确定身份用户的人脸特征进行比对识别，能提高识别的正确率。The face recognition method and device provided in the embodiments of the present application are applicable to the application scenario shown in FIG. 1. The application scenario shown in FIG. 1 includes a face recognition system 100 and a cloud server 200. The face recognition system 100 includes a server 10, an image acquisition device 20, at least one positioning device 30, and a robot 40. The cloud server 200 is loaded with a preset facial feature database, which includes the facial features of known users and user information (such as a user identity). The image acquisition device 20 is configured to acquire an image of a user and send the image to the server 10. The positioning device 30 is configured to locate a related user, and obtain user information of the related user and send it to the server 10. The server 10 reduces the preset facial feature database according to the information sent by the positioning device 30 to obtain a facial feature comparison range that includes only the facial features of the relevant user. The server 10 identifies the face image in the image of the identified user, and uses an algorithm to perform face feature extraction on the face image of the identified user (for example, based on a pre-trained neural network model, extracts face features from the face image) ), And then comparing and identifying the facial features based on the facial feature comparison range to confirm the identity of the user to be identified. The use of narrowed facial feature comparison range to compare and recognize the facial features of the identified users can improve the accuracy of recognition.
其中，图像采集装置20可以为摄像头、摄像机、照相机、扫描仪，或者其他带有拍照功能的设备(智能手机、平板电脑等)。定位装置30例如基站、WIFI定位装置等。机器人40可以为固定位置机器人也可以为可移动的机器人。人脸识别算法例如基于人脸特征点的识别算法、基于整幅人脸图像的识别算法、基于模板的识别算法和基于神经网络的识别算法等。The image acquisition device 20 may be a camera, a video camera, a camera, a scanner, or other devices (smartphones, tablets, etc.) with a photographing function. The positioning device 30 is, for example, a base station, a WIFI positioning device, or the like. The robot 40 may be a fixed-position robot or a movable robot. Face recognition algorithms are, for example, recognition algorithms based on facial feature points, recognition algorithms based on entire face images, recognition algorithms based on templates, and recognition algorithms based on neural networks.
以上仅示例性的示出了应用场景的一种形式，在其他应用场景中，也可以不使用云端服务器200，而将预设人脸特征库装载在本地人脸识别***100的服 务器10中。图像采集装置20可以单独设置(例如设置在房间门口)，也可以集成在机器人40上。服务器10、图像采集装置20、定位装置30和机器人40的数量可以为一个也可以为多个。The above only exemplarily shows one form of the application scenario. In other application scenarios, the cloud server 200 may not be used, and the preset face feature database may be loaded into the server 10 of the local face recognition system 100. The image acquisition device 20 may be provided separately (for example, at the door of a room), or may be integrated on the robot 40. The number of the server 10, the image acquisition device 20, the positioning device 30, and the robot 40 may be one or more.
图2为本申请实施例提供的人脸识别方法的一个实施例的流程图，所述人脸识别方法可由图1中的服务器10执行，如图2所示，所述人脸识别方法包括：FIG. 2 is a flowchart of an embodiment of a face recognition method according to an embodiment of the present application. The face recognition method may be executed by the server 10 in FIG. 1. As shown in FIG.
101：获取待确定身份用户的人脸图像，基于所述人脸图像进行识别获得所述人脸图像的人脸特征。101: Obtain a face image of a user whose identity is to be determined, and perform recognition based on the face image to obtain a face feature of the face image.
可以通过图像采集装置20采集待确定身份用户的图像，服务器10接收到待确定身份用户的图像后，识别所述图像中的人脸图像，并利用算法对待确定身份用户的人脸图像进行人脸特征提取，例如基于预先训练好的神经网络模型对人脸图像进行人脸特征提取。The image of the to-be-identified user may be collected by the image acquisition device 20. After receiving the image of the to-be-identified user, the server 10 recognizes the face image in the image and uses an algorithm to perform a face treatment on the face image of the to-be-identified user Feature extraction, for example, extracting face features from a face image based on a pre-trained neural network model.
102：获取定位装置的定位信息，基于所述定位信息从预设人脸特征库中获得人脸特征比对范围，所述预设人脸特征库和所述人脸特征比对范围均包括已知用户的人脸特征和用户信息，所述人脸特征比对范围包括的人脸数量小于所述预设人脸特征库中包括的人脸数量。102: Obtain positioning information of a positioning device, and obtain a facial feature comparison range from a preset facial feature database based on the positioning information. The preset facial feature database and the facial feature comparison range both include Knowing the user's face features and user information, the number of faces included in the face feature comparison range is less than the number of faces included in the preset face feature database.
定位装置30定位相关用户，并获得定位信息发送给服务器10，其中定位信息包括用户的信息(例如用户的身份标识)。服务器10根据相关用户的信息对预设人脸特征库进行缩小，获得只包括相关用户的人脸特征的人脸特征比对范围。The positioning device 30 locates the relevant user, and obtains the positioning information and sends it to the server 10, where the positioning information includes the user's information (such as the user's identity). The server 10 reduces the preset facial feature database according to the information of the related user, and obtains a facial feature comparison range including only the facial features of the related user.
其中，在一些实施例中，定位装置30可以包括第一基站和第二基站，人脸特征比对范围包括第一人脸特征比对范围和第二人脸特征比对范围。服务器10通过第一基站定位到的定位信息从预设人脸特征库中获得第一人脸特征比对范围，通过第二基站定位到的信息从预设人脸特征库中获得第二人脸特征比对范围。具体的，第一基站和第二基站可以通过定位用户携带的手机等电子设备定位用户的位置，从而获得出现在某一区域的相关用户。In some embodiments, the positioning device 30 may include a first base station and a second base station, and the facial feature comparison range includes a first facial feature comparison range and a second facial feature comparison range. The server 10 obtains a first face feature comparison range from a preset face feature database by using the positioning information located by the first base station, and obtains a second face from the preset face feature database by using the information located by the second base station. Feature comparison range. Specifically, the first base station and the second base station can locate the position of the user by locating an electronic device such as a mobile phone carried by the user, so as to obtain related users who appear in a certain area.
本申请实施例的人脸识别方法可以适用于多种人脸识别的场景，包括各种营业厅(例如电信营业厅、售票厅或其他营业厅)、火车站、飞机场等。在其中一些应用场景中，第一基站可以是设置在室内的基站，第二基站可以是设置在室外的基站。第一基站定位出当前时间(例如当前一段时间或者当前时刻) 所述室内的用户，并将用户的信息(例如用户的身份标识)发送给服务器10，服务器10根据该信息从预设人脸特征库中找出室内用户的人脸特征作为第一人脸特征比对范围。The face recognition method in the embodiment of the present application can be applied to a variety of face recognition scenarios, including various business halls (such as telecommunication business halls, ticket sales halls, or other business halls), railway stations, and airports. In some of these application scenarios, the first base station may be a base station installed indoors, and the second base station may be a base station installed outdoors. The first base station locates a user in the room at the current time (for example, the current time or the current time), and sends the user's information (for example, the user's identity) to the server 10, and the server 10 uses the preset face characteristics Find the facial features of indoor users in the database as the first facial feature comparison range.
第二基站设置的目的是找出最有可能来所述室内办理业务的人，第二基站的定位方法可以根据具体应用场景调整。在一些应用场景中，第二基站可以定位获得在第一预设时段内在预设区域内出现的用户的信息，并将该信息发送给服务器10。其中，第一预设时段和预设区域可以事先设定，第一预设时段例如一年、半年、一个月或其他时间，预设区域可以是所述室内附近的一定区域，例如所述室内方圆五公里内，第二基站发送给服务器10的信息可以包括用户的身份标识、出现时间等。用户的身份标识可以是SIM卡标记用户身份的唯一标识，例如手机号码。服务器10根据第二基站的定位信息确定在该区域内出现时间较多(例如一个月内出现20天或者半年内出现两个月)的用户(有可能是该地区的常驻用户)，并获得这些用户的信息为第一用户信息。服务器10再获取第二预设时段(例如一个月)内来过所述室内办理业务的用户，并获得这些用户的信息为第二用户信息。服务器10将第一用户信息和第二用户信息取交集获得第三用户信息，并根据第三用户信息获得第二人脸特征比对范围。The purpose of setting the second base station is to find the person who is most likely to handle the business indoors. The positioning method of the second base station can be adjusted according to the specific application scenario. In some application scenarios, the second base station may locate and obtain information of a user appearing in a preset area within the first preset period, and send the information to the server 10. The first preset time period and the preset area can be set in advance. The first preset time period is, for example, one year, half a year, one month, or other time. The preset area can be a certain area near the indoor area, such as the indoor area. Within five kilometers of the circle, the information sent by the second base station to the server 10 may include the user's identity, appearance time, and so on. The user's identity can be a unique identifier that the SIM card uses to mark the user's identity, such as a mobile phone number. The server 10 determines, based on the positioning information of the second base station, users (such as 20 days in one month or two months in half a year) that appear more frequently in the area, and obtains The information of these users is the first user information. The server 10 then acquires users who have handled the business indoors within a second preset period (for example, one month), and obtains the information of these users as the second user information. The server 10 obtains the third user information by intersecting the first user information and the second user information, and obtains the second facial feature comparison range according to the third user information.
其中，在实际应用中，第一人脸特征比对范围和第二人脸特征比对范围可以是服务器10从预设人脸特征库中获取的数据子库，也可以仍存在于预设人脸特征库中，仅通过标签与预设人脸特征库中的其他数据相区分。Wherein, in actual applications, the first face feature comparison range and the second face feature comparison range may be a data sub-database obtained by the server 10 from a preset face feature library, or may still exist in the preset person. In the facial feature database, only labels are used to distinguish them from other data in the preset facial feature database.
在另一些实施例中，定位装置30也可以仅包括一类基站，例如设置在室内的基站或者设置在室外一定区域内的基站。服务器10根据该基站的定位信息从预设人脸特征库中仅获得一个人脸特征比对范围。当然，在其他实施例中，人脸特征比对范围也可以包括更多的比对范围，例如第一人脸特征比对范围、第二人脸特征比对范围和第三人脸特征比对范围等等，本申请实施例不作限定。In other embodiments, the positioning device 30 may include only one type of base station, for example, a base station installed indoors or a base station installed in a certain area outdoors. The server 10 obtains only one face feature comparison range from a preset face feature database according to the positioning information of the base station. Of course, in other embodiments, the facial feature comparison range may also include more comparison ranges, such as the first face feature comparison range, the second face feature comparison range, and the third face feature comparison. The scope and the like are not limited in the embodiments of the present application.
103：将所述人脸特征基于所述人脸特征比对范围进行识别，并根据识别结果指示机器人对待确定身份用户进行询问。103: Identify the facial features based on the facial feature comparison range, and instruct the robot to inquire about the identified user according to the recognition result.
在人脸特征比对范围包括第一人脸特征比对范围和第二人脸特征比对范围的场合，将第一人脸特征比对范围设置成包括室内用户的人脸特征，很大的缩小了人脸特征比对范围。只要用户进入所述室内时被第一基站定位到，其人脸特征就能进入第一人脸特征比对范围，则服务器10能快速准确的基于第一人脸 特征比对范围识别出待确定身份用户。如果通过第一人脸特征比对范围比对的初级识别结果中，具有相似度大于或者等于第一预设阈值的人脸特征，则确认用户的身份为其中相似度最高的人脸特征对应的用户，则无需再将所述人脸特征与第二人脸特征比对范围进行比对。When the facial feature comparison range includes the first facial feature comparison range and the second facial feature comparison range, the first facial feature comparison range is set to include the facial features of indoor users. Reduce the range of facial feature comparison. As long as the user is located by the first base station when entering the room, his face features can enter the first face feature comparison range, and the server 10 can quickly and accurately identify the to-be-determined based on the first face feature comparison range. Identity user. If the primary recognition result of the first facial feature comparison range comparison has facial features with a similarity greater than or equal to a first preset threshold, it is confirmed that the identity of the user corresponds to the facial feature with the highest similarity. The user does not need to compare the facial feature comparison range with the second facial feature comparison.
但对一些未带手机或其他电子设备的用户，即使该用户进入所述室内，第一基站也将定位不到该用户，则通过第一人脸特征比对范围将识别不出该用户(即识别结果的相似度均小于第一预设阈值)。针对这些用户，服务器10可以再将用户的人脸特征与第二人脸特征比对范围进行对比，如果识别结果中存在相似度大于或者等于第一预设阈值的人脸特征，则确认用户的身份为其中相似度最高的人脸特征对应的用户。如果识别结果中最大相似度大于第二预设阈值且小于第一预设阈值，则可以获得相似度位于前几位(例如前三位)的人脸特征对应的用户，然后指示机器人40对待确定身份用户进行询问，确认其是否是上述相似度最高的用户之一。具体的，询问方式可以以选择问句的方式提出。例如服务器10获得相似度最高的几个用户身份分别是李XX、张XX和王XX，则机器人40可以询问待确定身份用户，“你是李先生、张先生还是王先生”？通过待确定身份用户的肯定或者否定回答可以确定待确定身份用户的身份。这种选择式的询问方式，可以给用户亲切感，提高用户体验。However, for some users without mobile phones or other electronic devices, even if the user enters the room, the first base station will not be able to locate the user, and the user will not be identified through the first facial feature comparison range (i.e. The similarities of the recognition results are all smaller than the first preset threshold). For these users, the server 10 may then compare the user's face features with the second face feature comparison range. If there are face features with similarity greater than or equal to the first preset threshold in the recognition result, then confirm the user ’s The identity is the user corresponding to the face feature with the highest similarity. If the maximum similarity in the recognition result is greater than the second preset threshold value and less than the first preset threshold value, users corresponding to the facial features in the first few (such as the first three) similarities can be obtained, and then the robot 40 is instructed to determine The identity user asks if he is one of the users with the highest similarity. Specifically, the questioning manner can be presented in a manner of selecting a question. For example, the identities of the users with the highest similarity obtained by the server 10 are Li XX, Zhang XX, and Wang XX, respectively. Then the robot 40 may ask the user to be identified, "Are you Mr. Li, Mr. Zhang, or Mr. Wang?" The identity of the user to be identified can be determined by an affirmative or negative answer of the user to be identified. This selective inquiry method can give users a sense of intimacy and improve the user experience.
在其中一些实施例中，请参照图3，如果待确定身份用户的回答是肯定的答案，例如用户回答“我是李XX”，机器人40将待确定身份用户的回答结果发送给服务器10，服务器10根据待确定身份用户的回答结果提取该待确定身份用户的人脸特征，并将该待确定身份用户的人脸特征、用户身份信息和照片上传到预设人脸特征库，以提高下次的识别正确率。In some of these embodiments, please refer to FIG. 3, if the answer of the user to be identified is affirmative, for example, the user answers "I am Li XX", the robot 40 sends the answer result of the user to be identified to the server 10, the server 10 According to the answer result of the to-be-identified user, extract the facial features of the to-be-identified user, and upload the to-be-identified user ’s face features, user identity information, and photos to a preset face feature database to improve the next time. Recognition accuracy.
如果通过第二人脸特征比对范围获得的识别结果的相似度均小于或者等于第二预设阈值，则服务器10可以直接指示机器人40询问该待确定身份用户的用户信息，然后根据该用户的信息在预设人脸特征库中搜索到该用户对应的人脸特征，并将获得的人脸特征与该用户的人脸特征进行比对，以确定该用户的身份。If the similarity of the recognition results obtained through the second face feature comparison range is less than or equal to the second preset threshold, the server 10 may directly instruct the robot 40 to query the user information of the user whose identity is to be determined, and then according to the user ’s The information searches the preset facial feature database for the corresponding facial feature of the user, and compares the obtained facial feature with the facial feature of the user to determine the identity of the user.
在人脸特征比对范围仅包括一个人脸特征比对范围的场合，如果通过该人脸特征比对范围获得的识别结果中，存在相似度大于或者等于第一预设阈值的人脸特征，则确认待确定身份用户的身份为其中相似度最高的人脸特征对应的 用户。如果识别结果中最大相似度大于第二预设阈值且小于第一预设阈值，则可以获得相似度位于前几位(例如前三位)的人脸特征对应的用户，然后指示机器人40对待确定身份用户进行询问，确认其是否是上述相似度最高的用户之一。如果相似度均小于或者等于第二预设阈值，则服务器10可以直接指示机器人40询问该待确定身份用户的用户信息。In the case where the facial feature comparison range includes only one facial feature comparison range, if the recognition result obtained through the facial feature comparison range includes facial features with a degree of similarity greater than or equal to a first preset threshold, Then, it is confirmed that the identity of the to-be-identified user is the user corresponding to the face feature with the highest similarity. If the maximum similarity in the recognition result is greater than the second preset threshold value and less than the first preset threshold value, users corresponding to the facial features in the first few (such as the first three) similarities can be obtained, and then the robot 40 is instructed to determine The identity user asks if he is one of the users with the highest similarity. If the similarities are all less than or equal to the second preset threshold, the server 10 may directly instruct the robot 40 to query user information of the user whose identity is to be determined.
其中，第一预设阈值和第二预设阈值可以事先设定，例如第一预设阈值设置为60％，第二预设阈值设置为55％。The first preset threshold and the second preset threshold can be set in advance. For example, the first preset threshold is set to 60%, and the second preset threshold is set to 55%.
本申请实施例通过获取定位装置的定位信息，并根据所述定位信息从预设人脸特征库中获得人脸特征比对范围，将待确定身份用户的人脸特征基于所述人脸特征比对范围进行比对识别以识别待确定身份用户的身份。因为采用了相对于预设人脸特征库缩小的人脸特征比对范围，提高了识别正确率，同时还提供了识别速度。In the embodiment of the present application, by obtaining positioning information of a positioning device, and obtaining a facial feature comparison range from a preset facial feature database according to the positioning information, the facial features of a user to be identified are based on the facial feature ratio. Compare and identify the range to identify the identity of the user to be identified. Because the narrowed face feature comparison range compared to the preset face feature database is used, the recognition accuracy is improved, and the recognition speed is also provided.
相应的，本申请实施例还提供了一种人脸识别装置，所述人脸识别装置用于图1所示的服务器10，如图4所示，所述人脸识别装置400包括：Accordingly, an embodiment of the present application further provides a face recognition device. The face recognition device is used in the server 10 shown in FIG. 1. As shown in FIG. 4, the face recognition device 400 includes:
人脸特征获取模块401，用于获取待确定身份用户的人脸图像，基于所述人脸图像进行识别获得所述人脸图像的人脸特征；A face feature obtaining module 401, configured to obtain a face image of a user whose identity is to be determined, and obtain a face feature of the face image by performing recognition based on the face image;
人脸特征比对范围获取模块402，用于获取定位装置的定位信息，基于所述定位信息从预设人脸特征库中获得人脸特征比对范围，所述预设人脸特征库和所述人脸特征比对范围均包括已知用户的人脸特征和用户信息，所述人脸特征比对范围包括的人脸数量小于所述预设人脸特征库中包括的人脸数量；A facial feature comparison range acquisition module 402 is configured to acquire positioning information of a positioning device, and obtain a facial feature comparison range from a preset face feature database based on the positioning information, the preset face feature database and The face feature comparison range includes the face features and user information of a known user, and the face feature comparison range includes fewer faces than the number of faces included in the preset face feature database;
识别模块403，用于将所述人脸特征基于所述人脸特征比对范围进行识别，并根据识别结果指示机器人对所述待确定身份用户进行询问。The recognition module 403 is configured to recognize the facial features based on the facial feature comparison range, and instruct the robot to query the user to be identified according to the recognition result.
本申请实施例通过获取定位装置的定位信息，并根据所述定位信息从预设人脸特征库中获得人脸特征比对范围，将待确定身份用户的人脸特征基于所述人脸特征比对范围进行比对识别以识别待确定身份用户的身份。因为采用了相对于预设人脸特征库缩小的人脸特征比对范围，提高了识别正确率，同时还提供了识别速度。In the embodiment of the present application, by obtaining positioning information of a positioning device, and obtaining a facial feature comparison range from a preset facial feature database according to the positioning information, the facial features of a user to be identified are based on the facial feature ratio. Compare and identify the range to identify the identity of the user to be identified. Because the narrowed face feature comparison range compared to the preset face feature database is used, the recognition accuracy is improved, and the recognition speed is also provided.
在人脸识别装置400的一些实施例中，识别模块403具体用于：In some embodiments of the face recognition device 400, the recognition module 403 is specifically configured to:
如果识别结果的相似度满足预设条件，则获得识别结果中相似度最高的至 少一个人脸特征，指示机器人基于该至少一个人脸特征对应的用户身份信息进行询问。If the similarity of the recognition result satisfies a preset condition, at least one face feature with the highest similarity in the recognition result is obtained, and the robot is instructed to make an inquiry based on the user identity information corresponding to the at least one face feature.
具体的，在其中一些实施例中，识别模块403具体用于：Specifically, in some of these embodiments, the identification module 403 is specifically configured to:
如果识别结果中最大相似度大于第二预设阈值且小于第一预设阈值，则获得识别结果中相似度最高的至少一个人脸特征，指示机器人基于该至少一个人脸特征的用户身份信息进行询问；If the maximum similarity in the recognition result is greater than the second preset threshold value and less than the first preset threshold value, at least one face feature with the highest similarity in the recognition result is obtained, and the robot is instructed to perform based on the user identity information of the at least one face feature. ask;
如果识别结果中最大相似度小于或者等于第二预设阈值，则指示机器人询问所述待确定身份用户的用户身份信息。If the maximum similarity in the recognition result is less than or equal to the second preset threshold, the robot is instructed to query the user identity information of the user whose identity is to be determined.
在人脸识别装置400的一些实施例中，请参照图5，所述定位装置包括第一基站和第二基站，所述人脸特征比对范围包括第一人脸特征比对范围和第二人脸特征比对范围；In some embodiments of the face recognition device 400, please refer to FIG. 5, the positioning device includes a first base station and a second base station, and the face feature comparison range includes a first face feature comparison range and a second Facial feature comparison range;
人脸特征比对范围获取模块402包括：The facial feature comparison range acquisition module 402 includes:
第一人脸特征比对范围获取子模块4021，用于获取所述第一基站的定位信息，基于所述第一基站的定位信息从预设人脸特征库中获得第一人脸特征比对范围；A first facial feature comparison range acquisition submodule 4021 is configured to acquire positioning information of the first base station, and obtain a first facial feature comparison from a preset facial feature database based on the positioning information of the first base station. range;
第二人脸特征比对范围获取子模块4022，用于获取所述第二基站的定位信息，基于所述第二基站的定位信息从预设人脸特征库中获得第二人脸特征比对范围；A second facial feature comparison range acquisition submodule 4022 is configured to acquire positioning information of the second base station, and obtain a second facial feature comparison from a preset facial feature database based on the positioning information of the second base station. range;
识别模块403还具体用于：The identification module 403 is further specifically configured to:
将所述人脸特征基于所述第一人脸特征比对范围进行识别，获得初级识别结果，如果初级识别结果中具有相似度大于或者等于第一预设阈值的人脸特征，则根据相似度最高的人脸特征确认所述待确定身份用户的身份；Identify the face feature based on the first face feature comparison range to obtain a primary recognition result, and if the primary recognition result has a face feature with a similarity greater than or equal to a first preset threshold, the The highest facial feature confirms the identity of the user to be identified;
如果初级识别结果的相似度均小于第一预设阈值，则将所述人脸特征基于所述第二人脸特征比对范围进行识别，获得识别结果。If the similarities of the primary recognition results are less than the first preset threshold, the facial features are identified based on the second facial feature comparison range to obtain a recognition result.
其中，在人脸识别装置400的一些实施例中，所述第一基站为室内的基站，所述第二基站为室外基站；In some embodiments of the face recognition device 400, the first base station is an indoor base station, and the second base station is an outdoor base station;
第一人脸特征比对范围获取子模块4021具体用于：The first facial feature comparison range acquisition sub-module 4021 is specifically configured to:
获取所述第一基站通过实时定位获取的位于所述室内的用户的用户信息，根据所述用户信息在预设人脸特征库中获得第一人脸特征比对范围。Acquiring user information of a user located in the room, obtained by the first base station through real-time positioning, and obtaining a first facial feature comparison range in a preset facial feature database according to the user information.
第二人脸特征比对范围获取子模块4022具体用于：The second facial feature comparison range acquisition sub-module 4022 is specifically configured to:
获取所述第二基站的定位信息，所述第二基站的定位信息包括在第一预设时段内、在预设区域内出现的用户的信息，根据所述第二基站的定位信息获得第一用户信息，所述第一用户信息为在第一预设时段内、在所述预设区域内出现的时间超过预设时间阈值的用户的信息；Acquiring positioning information of the second base station, where the positioning information of the second base station includes information of a user appearing in a preset area within a first preset period, and obtaining the first according to the positioning information of the second base station User information, where the first user information is information of a user who appears in the preset area for a first preset period of time and exceeds a preset time threshold;
获取第二用户信息，所述第二用户信息为第二预设时段内、来过所述室内的用户的信息；Acquiring second user information, where the second user information is information of a user who has visited the room within a second preset period;
将所述第一用户信息和所述第二用户信息取交集，获得第三用户信息，根据所述第三用户信息在所述预设人脸特征库中获得第二人脸特征比对范围。Intersect the first user information and the second user information to obtain third user information, and obtain a second face feature comparison range in the preset face feature database according to the third user information.
在人脸识别装置400的其他实施例中，请参照图5，人脸识别装置400还包括：In another embodiment of the face recognition device 400, please refer to FIG. 5. The face recognition device 400 further includes:
上传模块404，用于接收机器人发送的用户确认消息，根据所述用户确认消息将所述待确定身份用户的人脸特征、用户身份信息和图像上传所述预设人脸特征库。The uploading module 404 is configured to receive a user confirmation message sent by the robot, and upload, according to the user confirmation message, the facial features, user identity information, and images of the user whose identity is to be determined to the preset facial feature database.
需要说明的是，上述人脸识别装置可执行本申请实施例所提供的人脸识别方法，具备执行方法相应的功能模块和有益效果。未在人脸识别装置实施例中详尽描述的技术细节，可参见本申请实施例所提供的人脸识别方法。It should be noted that the above-mentioned face recognition device can execute the face recognition method provided in the embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method. For technical details not described in detail in the embodiment of the face recognition device, refer to the face recognition method provided in the embodiment of the present application.
图6是本申请实施例提供的服务器10的硬件结构示意图，如图6所示，该服务器10包括：FIG. 6 is a schematic diagram of a hardware structure of a server 10 according to an embodiment of the present application. As shown in FIG. 6, the server 10 includes:
一个或多个处理器11以及存储器12，图6中以一个处理器11为例。One or more processors 11 and a memory 12. One processor 11 is taken as an example in FIG. 6.
处理器11和存储器12可以通过总线或者其他方式连接，图6中以通过总线连接为例。The processor 11 and the memory 12 may be connected through a bus or in other manners. In FIG. 6, the connection through the bus is taken as an example.
存储器12作为一种非易失性计算机可读存储介质，可用于存储非易失性软件程序、非易失性计算机可执行程序以及模块，如本申请实施例中的人脸识别方法对应的程序指令/模块(例如，附图4所示的人脸特征获取模块401、人脸特征比对范围获取模块402和识别模块403)。处理器11通过运行存储在存储器12中的非易失性软件程序、指令以及模块，从而执行服务器的各种功能应用以及数据处理，即实现上述方法实施例的人脸识别方法。The memory 12 is a non-volatile computer-readable storage medium and can be used to store non-volatile software programs, non-volatile computer executable programs, and modules, such as programs corresponding to the face recognition method in the embodiments of the present application. Instructions / modules (for example, the facial feature acquisition module 401, the facial feature comparison range acquisition module 402, and the recognition module 403 shown in FIG. 4). The processor 11 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions, and modules stored in the memory 12, that is, the face recognition method of the above method embodiment is implemented.
存储器12可以包括存储程序区和存储数据区，其中，存储程序区可存储操 作***、至少一个功能所需要的应用程序；存储数据区可存储根据人脸识别装置的使用所创建的数据等。此外，存储器12可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件、闪存器件、或其他非易失性固态存储器件。在一些实施例中，存储器12可选包括相对于处理器11远程设置的存储器，这些远程存储器可以通过网络连接至人脸识别装置。上述网络的实例包括但不限于互联网、企业内部网、局域网、移动通信网及其组合。The memory 12 may include a storage program area and a storage data area, wherein the storage program area may store an operating system and an application program required for at least one function; the storage data area may store data created according to the use of the face recognition device and the like. In addition, the memory 12 may include a high-speed random access memory, and may further include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 12 may optionally include a memory remotely disposed with respect to the processor 11, and these remote memories may be connected to the face recognition device through a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.
所述一个或者多个模块存储在所述存储器12中，当被所述一个或者多个处理器11执行时，执行上述任意方法实施例中的人脸识别方法，例如，执行以上描述的图2中的方法步骤101至步骤103，图3中的方法步骤201至步骤205；实现图4中的模块401-403、图5中模块401-404、子模块4021-4022的功能。The one or more modules are stored in the memory 12, and when executed by the one or more processors 11, execute the face recognition method in any of the above method embodiments, for example, execute FIG. 2 described above. The method includes steps 101 to 103 in the method, steps 201 to 205 in the method in FIG. 3, and implements the functions of modules 401-430 in FIG. 4, modules 401-404 in FIG.
上述产品可执行本申请实施例所提供的方法，具备执行方法相应的功能模块和有益效果。未在本实施例中详尽描述的技术细节，可参见本申请实施例所提供的方法。The above product can execute the method provided in the embodiment of the present application, and has corresponding function modules and beneficial effects of executing the method. For technical details not described in detail in this embodiment, reference may be made to the method provided in the embodiment of the present application.
本申请实施例提供了一种非易失性计算机可读存储介质，所述计算机可读存储介质存储有计算机可执行指令，该计算机可执行指令被一个或多个处理器执行，例如图7中的一个处理器11，可使得上述一个或多个处理器可执行上述任意方法实施例中的人脸识别方法，例如，执行以上描述的图2中的方法步骤101至步骤103，图3中的方法步骤201至步骤205；实现图4中的模块401-403、图5中模块401-404、子模块4021-4022的功能。An embodiment of the present application provides a non-volatile computer-readable storage medium. The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are executed by one or more processors, for example, as shown in FIG. 7. A processor 11 may enable the one or more processors to execute the face recognition method in any of the foregoing method embodiments, for example, to execute the method steps 101 to 103 in FIG. 2 described above, and the steps in FIG. 3 Steps 201 to 205 of the method; the functions of modules 401-403 in FIG. 4, modules 401-404 in FIG. 5, and sub-modules 4021-4022 are implemented.
以上所描述的装置实施例仅仅是示意性的，其中所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。The device embodiments described above are only schematic, and the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located One place, or it can be distributed across multiple network elements. Some or all of the modules may be selected according to actual needs to achieve the objective of the solution of this embodiment.
通过以上的实施方式的描述，本领域普通技术人员可以清楚地了解到各实施方式可借助软件加通用硬件平台的方式来实现，当然也可以通过硬件。本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程是可以通过计算机程序来指令相关的硬件来完成，所述的程序可存储于一计算机可读取存储介质中，该程序在执行时，可包括如上述各方法的实施例的流程。其中，所 述的存储介质可为磁碟、光盘、只读存储记忆体(Read-Only Memory,ROM)或随机存储记忆体(RandomAccessMemory,RAM)等。Through the description of the above embodiments, those skilled in the art can clearly understand that the embodiments can be implemented by means of software plus a general hardware platform, and of course, they can also be implemented by hardware. A person of ordinary skill in the art can understand that all or part of the processes in the method of the foregoing embodiment can be completed by using a computer program to instruct related hardware. The program can be stored in a computer-readable storage medium. When executed, the processes of the embodiments of the methods described above may be included. The storage medium may be a magnetic disk, an optical disk, a read-only memory (Read-Only Memory, ROM), or a random access memory (Random Access Memory, RAM).
最后应说明的是：以上实施例仅用以说明本申请的技术方案，而非对其限制；在本申请的思路下，以上实施例或者不同实施例中的技术特征之间也可以进行组合，步骤可以以任意顺序实现，并存在如上所述的本申请的不同方面的许多其它变化，为了简明，它们没有在细节中提供；尽管参照前述实施例对本申请进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的范围。Finally, it should be noted that the above embodiments are only used to describe the technical solution of the present application, but not limited thereto; under the idea of the present application, the technical features in the above embodiments or different embodiments may also be combined, The steps can be implemented in any order, and there are many other variations of the different aspects of the application as described above, for the sake of brevity, they are not provided in the details; although the application is described in detail with reference to the foregoing embodiments, it is common in the art The technician should understand that it can still modify the technical solutions described in the foregoing embodiments, or equivalently replace some of the technical features; and these modifications or replacements do not deviate the essence of the corresponding technical solutions from the implementation of this application. Examples of technical solutions.

Claims (17)

  1. 一种人脸识别方法，所述人脸识别方法应用于服务器，其特征在于，所述方法包括：A face recognition method, which is applied to a server, is characterized in that the method includes:
    获取待确定身份用户的人脸图像，基于所述人脸图像进行识别获得所述人脸图像的人脸特征；Obtaining a face image of a user whose identity is to be determined, and identifying based on the face image to obtain a face feature of the face image;
    获取定位装置的定位信息，基于所述定位信息从预设人脸特征库中获得人脸特征比对范围，所述预设人脸特征库和所述人脸特征比对范围均包括已知用户的人脸特征和用户信息，所述人脸特征比对范围包括的人脸数量小于所述预设人脸特征库中包括的人脸数量；Acquire positioning information of a positioning device, and obtain a facial feature comparison range from a preset facial feature database based on the positioning information, both of the preset facial feature database and the facial feature comparison range include known users Facial feature and user information, the facial feature comparison range includes fewer faces than the number of faces included in the preset face feature database;
    将所述人脸特征基于所述人脸特征比对范围进行识别，并根据识别结果指示机器人对所述待确定身份用户进行询问。Identify the face feature based on the face feature comparison range, and instruct the robot to query the user to be identified according to the recognition result.
  2. 根据权利要求1所述的方法，其特征在于，所述根据识别结果指示机器人对所述待确定身份用户进行询问，包括：The method according to claim 1, wherein the instructing the robot to query the user to be identified according to the recognition result comprises:
    如果识别结果的相似度满足预设条件，则获得识别结果中相似度最高的至少一个人脸特征，指示机器人基于该至少一个人脸特征对应的用户身份信息进行询问。If the similarity of the recognition result satisfies a preset condition, at least one face feature with the highest similarity in the recognition result is obtained, and the robot is instructed to make an inquiry based on the user identity information corresponding to the at least one face feature.
  3. 根据权利要求2所述的方法，其特征在于，所述识别结果的相似度满足预设条件，包括：The method according to claim 2, wherein the similarity of the recognition results satisfies a preset condition, comprising:
    识别结果中最大相似度大于第二预设阈值且小于第一预设阈值；The maximum similarity in the recognition result is larger than the second preset threshold and smaller than the first preset threshold;
    所述根据识别结果指示机器人对所述待确定身份用户进行询问，还包括：The instructing the robot to inquire the user whose identity is to be determined according to the recognition result further includes:
    如果识别结果中最大相似度小于或者等于第二预设阈值，则指示机器人询问所述待确定身份用户的用户身份信息。If the maximum similarity in the recognition result is less than or equal to the second preset threshold, the robot is instructed to query the user identity information of the user whose identity is to be determined.
  4. 根据权利要求1-3任意一项所述的方法，其特征在于，所述定位装置包括第一基站和第二基站，所述人脸特征比对范围包括第一人脸特征比对范围和第二人脸特征比对范围；The method according to any one of claims 1-3, wherein the positioning device comprises a first base station and a second base station, and the facial feature comparison range includes a first facial feature comparison range and a first base station. Comparison range of two facial features;
    所述获取定位装置的定位信息，基于所述定位信息从预设人脸特征库中获得人脸特征比对范围，包括：The acquiring positioning information of a positioning device and obtaining a facial feature comparison range from a preset facial feature database based on the positioning information includes:
    获取所述第一基站的定位信息，基于所述第一基站的定位信息从预设人脸 特征库中获得第一人脸特征比对范围；Acquiring positioning information of the first base station, and obtaining a first facial feature comparison range from a preset facial feature database based on the positioning information of the first base station;
    获取所述第二基站的定位信息，基于所述第二基站的定位信息从预设人脸特征库中获得第二人脸特征比对范围；Acquiring positioning information of the second base station, and obtaining a second facial feature comparison range from a preset facial feature database based on the positioning information of the second base station;
    所述将所述人脸特征基于所述人脸特征比对范围进行识别，包括：The identifying the facial features based on the facial feature comparison range includes:
    将所述人脸特征基于所述第一人脸特征比对范围进行识别，获得初级识别结果，如果初级识别结果中具有相似度大于或者等于第一预设阈值的人脸特征，则根据相似度最高的人脸特征确认所述待确定身份用户的身份；Identify the face feature based on the first face feature comparison range to obtain a primary recognition result, and if the primary recognition result has a face feature with a similarity greater than or equal to a first preset threshold, then based on the similarity The highest facial feature confirms the identity of the user to be identified;
    如果初级识别结果的相似度均小于第一预设阈值，则将所述人脸特征基于所述第二人脸特征比对范围进行识别，获得识别结果。If the similarities of the primary recognition results are less than the first preset threshold, the facial features are identified based on the second facial feature comparison range to obtain a recognition result.
  5. 根据权利要求4所述的方法，其特征在于，所述第一基站为室内的基站，所述第二基站为室外基站；The method according to claim 4, wherein the first base station is an indoor base station, and the second base station is an outdoor base station;
    所述获取所述第一基站的定位信息，基于所述第一基站的定位信息从预设人脸特征库中获得第一人脸特征比对范围，包括：The acquiring the positioning information of the first base station and obtaining the first facial feature comparison range from a preset facial feature database based on the positioning information of the first base station includes:
    获取所述第一基站通过实时定位获取的位于所述室内的用户的用户信息，根据所述用户信息在预设人脸特征库中获得第一人脸特征比对范围。Acquiring user information of a user located in the room, obtained by the first base station through real-time positioning, and obtaining a first facial feature comparison range in a preset facial feature database according to the user information.
  6. 根据权利要求4或5所述的方法，其特征在于，所述获取所述第二基站的定位信息，基于所述第二基站的定位信息从预设人脸特征库中获得第二人脸特征比对范围，包括：The method according to claim 4 or 5, wherein the acquiring the positioning information of the second base station, and obtaining the second facial feature from a preset facial feature database based on the positioning information of the second base station Comparison range, including:
    获取所述第二基站的定位信息，所述第二基站的定位信息包括在第一预设时段内、在预设区域内出现的用户的信息，根据所述第二基站的定位信息获得第一用户信息，所述第一用户信息为在第一预设时段内、在所述预设区域内出现的时间超过预设时间阈值的用户的信息；Acquiring positioning information of the second base station, where the positioning information of the second base station includes information of a user appearing in a preset area within a first preset period, and obtaining the first according to the positioning information of the second base station User information, where the first user information is information of a user who appears in the preset area for a first preset period of time and exceeds a preset time threshold;
    获取第二用户信息，所述第二用户信息为第二预设时段内、来过所述室内的用户的信息；Acquiring second user information, where the second user information is information of a user who has visited the room within a second preset period;
    将所述第一用户信息和所述第二用户信息取交集，获得第三用户信息，根据所述第三用户信息在所述预设人脸特征库中获得第二人脸特征比对范围。Intersect the first user information and the second user information to obtain third user information, and obtain a second face feature comparison range in the preset face feature database according to the third user information.
  7. 根据权利要求2所述的方法，其特征在于，所述方法还包括：The method according to claim 2, further comprising:
    接收机器人发送的用户确认消息，根据所述用户确认消息将所述待确定身份用户的人脸特征、用户身份信息和图像上传所述预设人脸特征库。Receiving a user confirmation message sent by the robot, and uploading, according to the user confirmation message, the facial features, user identity information, and images of the user whose identity is to be determined to the preset facial feature database.
  8. 一种人脸识别装置，所述人脸识别装置应用于服务器，其特征在于，所述装置包括：A face recognition device, which is applied to a server, is characterized in that the device includes:
    人脸特征获取模块，用于获取待确定身份用户的人脸图像，基于所述人脸图像进行识别获得所述人脸图像的人脸特征；A face feature acquisition module, configured to obtain a face image of a user whose identity is to be determined, and obtain a face feature of the face image based on the recognition of the face image;
    人脸特征比对范围获取模块，用于获取定位装置的定位信息，基于所述定位信息从预设人脸特征库中获得人脸特征比对范围，所述预设人脸特征库和所述人脸特征比对范围均包括已知用户的人脸特征和用户信息，所述人脸特征比对范围包括的人脸数量小于所述预设人脸特征库中包括的人脸数量；A facial feature comparison range acquisition module is configured to obtain positioning information of a positioning device, and obtain a facial feature comparison range from a preset face feature database based on the positioning information, the preset face feature database and the The facial feature comparison range includes facial features and user information of a known user, and the facial feature comparison range includes fewer faces than the number of faces included in the preset face feature database;
    识别模块，用于将所述人脸特征基于所述人脸特征比对范围进行识别，并根据识别结果指示机器人对所述待确定身份用户进行询问。A recognition module, configured to recognize the facial feature based on the facial feature comparison range, and instruct the robot to query the user to be identified according to the recognition result.
  9. 根据权利要求8所述的装置，其特征在于，所述识别模块具体用于：The device according to claim 8, wherein the identification module is specifically configured to:
    如果识别结果的相似度满足预设条件，则获得识别结果中相似度最高的至少一个人脸特征，指示机器人基于该至少一个人脸特征对应的用户身份信息进行询问。If the similarity of the recognition result satisfies a preset condition, at least one face feature with the highest similarity in the recognition result is obtained, and the robot is instructed to make an inquiry based on the user identity information corresponding to the at least one face feature.
  10. 根据权利要求9所述的装置，其特征在于，所述识别模块具体用于：The device according to claim 9, wherein the identification module is specifically configured to:
    如果识别结果中最大相似度大于第二预设阈值且小于第一预设阈值，则获得识别结果中相似度最高的至少一个人脸特征，指示机器人基于该至少一个人脸特征的用户身份信息进行询问；If the maximum similarity in the recognition result is greater than the second preset threshold value and less than the first preset threshold value, at least one face feature with the highest similarity in the recognition result is obtained, and the robot is instructed to perform based on the user identity information of the at least one face feature. ask;
    如果识别结果中最大相似度小于或者等于第二预设阈值，则指示机器人询问所述待确定身份用户的用户身份信息。If the maximum similarity in the recognition result is less than or equal to the second preset threshold, the robot is instructed to query the user identity information of the user whose identity is to be determined.
  11. 根据权利要求8-10任意一项所述的装置，其特征在于，所述定位装置包括第一基站和第二基站，所述人脸特征比对范围包括第一人脸特征比对范围和第二人脸特征比对范围；The device according to any one of claims 8 to 10, wherein the positioning device comprises a first base station and a second base station, and the face feature comparison range includes a first face feature comparison range and a first base station. Comparison range of two facial features;
    所述人脸特征比对范围获取模块包括：The facial feature comparison range acquisition module includes:
    第一人脸特征比对范围获取子模块，用于获取所述第一基站的定位信息，基于所述第一基站的定位信息从预设人脸特征库中获得第一人脸特征比对范围；A first facial feature comparison range acquisition submodule, configured to obtain positioning information of the first base station, and obtain a first facial feature comparison range from a preset facial feature database based on the positioning information of the first base station ;
    第二人脸特征比对范围获取子模块，用于获取所述第二基站的定位信息，基于所述第二基站的定位信息从预设人脸特征库中获得第二人脸特征比对范围；A second facial feature comparison range acquisition submodule, configured to obtain positioning information of the second base station, and obtain a second facial feature comparison range from a preset facial feature database based on the positioning information of the second base station ;
    所述识别模块还具体用于：The identification module is further specifically configured to:
    将所述人脸特征基于所述第一人脸特征比对范围进行识别，获得初级识别结果，如果初级识别结果中具有相似度大于或者等于第一预设阈值的人脸特征，则根据相似度最高的人脸特征确认所述待确定身份用户的身份；Identify the face feature based on the first face feature comparison range to obtain a primary recognition result, and if the primary recognition result has a face feature with a similarity greater than or equal to a first preset threshold, then based on the similarity The highest facial feature confirms the identity of the user to be identified;
    如果初级识别结果的相似度均小于第一预设阈值，则将所述人脸特征基于所述第二人脸特征比对范围进行识别，获得识别结果。If the similarities of the primary recognition results are less than the first preset threshold, the facial features are identified based on the second facial feature comparison range to obtain a recognition result.
  12. 根据权利要求11所述的装置，其特征在于，所述第一基站为室内的基站，所述第二基站为室外基站；The apparatus according to claim 11, wherein the first base station is an indoor base station, and the second base station is an outdoor base station;
    所述第一人脸特征比对范围获取子模块具体用于：The first facial feature comparison range acquisition submodule is specifically configured to:
    获取所述第一基站通过实时定位获取的位于所述室内的用户的用户信息，根据所述用户信息在预设人脸特征库中获得第一人脸特征比对范围。Acquiring user information of a user located in the room, obtained by the first base station through real-time positioning, and obtaining a first facial feature comparison range in a preset facial feature database according to the user information.
  13. 根据权利要求11或12所述的装置，其特征在于，所述第二人脸特征比对范围获取子模块具体用于：The device according to claim 11 or 12, wherein the second facial feature comparison range acquisition submodule is specifically configured to:
    获取所述第二基站的定位信息，所述第二基站的定位信息包括在第一预设时段内、在预设区域内出现的用户的信息，根据所述第二基站的定位信息获得第一用户信息，所述第一用户信息为在第一预设时段内、在所述预设区域内出现的时间超过预设时间阈值的用户的信息；Acquiring positioning information of the second base station, where the positioning information of the second base station includes information of a user appearing in a preset area within a first preset period, and obtaining the first according to the positioning information of the second base station User information, where the first user information is information of a user who appears in the preset area for a first preset period of time and exceeds a preset time threshold;
    获取第二用户信息，所述第二用户信息为第二预设时段内、来过所述室内的用户的信息；Acquiring second user information, where the second user information is information of a user who has visited the room within a second preset period;
    将所述第一用户信息和所述第二用户信息取交集，获得第三用户信息，根据所述第三用户信息在所述预设人脸特征库中获得第二人脸特征比对范围。Intersect the first user information and the second user information to obtain third user information, and obtain a second face feature comparison range in the preset face feature database according to the third user information.
  14. 根据权利要求9所述的装置，其特征在于，所述装置还包括：The apparatus according to claim 9, further comprising:
    上传模块，用于接收机器人发送的用户确认消息，根据所述用户确认消息将所述待确定身份用户的人脸特征、用户身份信息和图像上传所述预设人脸特征库。The uploading module is configured to receive a user confirmation message sent by the robot, and upload the facial features, user identity information, and images of the user whose identity is to be determined to the preset facial feature database according to the user confirmation message.
  15. 一种服务器，其特征在于，包括：A server is characterized in that it includes:
    至少一个处理器；以及，At least one processor; and
    与所述至少一个处理器通信连接的存储器；其中，A memory connected in communication with the at least one processor; wherein,
    所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述 至少一个处理器执行，以使所述至少一个处理器能够执行权利要求1-7任一项所述的方法。The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can execute the one of claims 1-7. method.
  16. 一种非易失性计算机可读存储介质，其特征在于，所述计算机可读存储介质存储有计算机可执行指令，当所述计算机可执行指令被服务器执行时，使所述服务器执行执行权利要求1-7任一项所述的方法。A non-volatile computer-readable storage medium, characterized in that the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a server, the server executes claims. The method according to any one of 1-7.
  17. 一种计算机程序产品，其特征在于，所述计算机程序产品包括存储在非易失性计算机可读存储介质上的计算机程序，所述计算机程序包括程序指令，当所述程序指令被服务器执行时，使所述服务器执行权利要求1-7任一项所述的方法。A computer program product, characterized in that the computer program product includes a computer program stored on a non-volatile computer-readable storage medium, the computer program includes program instructions, and when the program instructions are executed by a server, The server is caused to perform the method according to any one of claims 1-7.
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