CN114173158A - Face recognition method, cloud device, client device, electronic device and medium - Google Patents
Face recognition method, cloud device, client device, electronic device and medium Download PDFInfo
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Abstract
The disclosure provides a face recognition method, a cloud device, a client device, an electronic device and a medium, relates to the technical field of artificial intelligence, particularly relates to a cloud computing technology, and can be applied to scenes such as cloud games. The specific implementation scheme is as follows: receiving a request for starting a face recognition function sent by a user through client equipment; wherein, the request for starting the face recognition function carries the identification of the current application program; according to the identification of the current application program, equipment information which is possessed by the cloud equipment for realizing the face recognition function is sent to the client equipment; receiving video stream data of a user acquired by client equipment based on equipment information; and carrying out face recognition on the user based on the video stream data of the user. The embodiment of the application can greatly improve the success rate of face recognition.
Description
Technical Field
The present disclosure relates to the field of artificial intelligence technologies, and further relates to a cloud computing technology, and in particular, to a face recognition method, a cloud device, a client device, an electronic device, and a medium, which can be applied to a scene such as a cloud game.
Background
The cloud game is a game mode based on cloud computing, all games run at a server side in a running mode of the cloud game, and a rendered game picture is compressed and then transmitted to a user through a network. At the client, the user's gaming device does not require any high-end processor and graphics card, but only basic video decompression capability.
In the cloud game scenario, in order to prevent the user from indulging in the game, it is generally necessary to activate a face recognition function. When the human face is identified at the cloud end, the real camera data are collected and transmitted back to the cloud camera for driving in a video streaming mode, so that the function of identifying the human face of the real mobile phone of the user at the cloud end is achieved. However, the pixel difference of the real camera is varied, and the width and height ratios of the videos acquired by different mobile phone cameras are also different, such as 480 × 800, 640 × 800 and the like. Due to the fact that the width-to-height ratios of videos collected by different user mobile phones are different, the video stream transmitted to the cloud end is stretched, and the success rate of face recognition is very low.
Disclosure of Invention
The disclosure provides a face recognition method, a cloud device, a client device, an electronic device and a medium.
In a first aspect, an embodiment of the present application provides a face recognition method, which is applied to a cloud device, and the method includes:
receiving a request for starting a face recognition function sent by a user through client equipment; wherein, the request for starting the face recognition function carries the identifier of the current application program;
according to the identification of the current application program, sending equipment information which is possessed by the cloud equipment for realizing the face recognition function to the client equipment;
receiving video stream data of the user acquired by the client device based on the device information;
and carrying out face recognition on the user based on the video stream data of the user.
In a second aspect, an embodiment of the present application further provides a face recognition method, which is applied to a client device, and the method includes:
receiving a face recognition instruction sent by a user through a current application program;
responding to the face recognition instruction and sending a request for starting a face recognition function to the cloud end equipment; wherein, the request for starting the face recognition function carries the identifier of the current application program;
receiving device information which is sent by the cloud device and is possessed by the cloud device for realizing the face recognition function;
collecting video stream data of the user based on the device information; and sending the video stream data of the user to the cloud end equipment, so that the cloud end equipment carries out face recognition on the user based on the video stream data of the user.
In a third aspect, an embodiment of the present application provides a cloud device, where the cloud device includes: the system comprises a first receiving module, a first sending module and a face recognition module; wherein the content of the first and second substances,
the first receiving module is used for receiving a request for starting a face recognition function, which is sent by a user through client equipment; wherein, the request for starting the face recognition function carries the identifier of the current application program;
the first sending module is configured to send, to the client device, device information that the cloud device has the face recognition function according to the identifier of the current application program;
the first receiving module is further configured to receive video stream data of the user, which is acquired by the client device based on the device information;
the face recognition module is used for carrying out face recognition on the user based on the video stream data of the user.
In a fourth aspect, an embodiment of the present application further provides a client device, where the client device includes: the second receiving module, the second sending module and the video acquisition module; wherein the content of the first and second substances,
the second receiving module is used for receiving a face recognition instruction sent by a user through a current application program;
the second sending module is used for responding to the face recognition instruction and sending a request for starting a face recognition function to the cloud end equipment; wherein, the request for starting the face recognition function carries the identifier of the current application program;
the second receiving module is further configured to receive device information, which is sent by the cloud device and is possessed by the cloud device for implementing the face recognition function;
the video acquisition module is used for acquiring video stream data of the user based on the equipment information; and sending the video stream data of the user to the cloud end equipment, so that the cloud end equipment carries out face recognition on the user based on the video stream data of the user.
In a fifth aspect, an embodiment of the present application further provides an electronic device, including:
one or more processors;
a memory for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors implement the face recognition method according to any embodiment of the present application.
In a sixth aspect, the present application provides a storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the face recognition method according to any embodiment of the present application.
In a seventh aspect, a computer program product is provided, which when executed by a computer device implements the face recognition method according to any embodiment of the present application.
According to the technical scheme, the technical problem that due to the fact that the width and the height of videos collected by different user mobile phones are different in proportion in the prior art, the video stream transmitted to the cloud end is stretched, and the success rate of face recognition is very low is solved.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
fig. 1 is a schematic flow chart of a first process of a face recognition method according to an embodiment of the present application;
fig. 2 is a second flow chart of the face recognition method according to the embodiment of the present application;
fig. 3 is a third flow chart of the face recognition method according to the embodiment of the present application;
fig. 4 is a fourth flowchart illustrating a face recognition method according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a cloud device provided in an embodiment of the present application;
fig. 6 is a schematic structural diagram of a client device provided in an embodiment of the present application;
fig. 7 is a block diagram of an electronic device for implementing a face recognition method according to an embodiment of the present application.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Example one
Fig. 1 is a first flowchart of a face recognition method according to an embodiment of the present disclosure, where the method may be executed by a cloud device, the cloud device may be implemented by software and/or hardware, and the cloud device may be integrated in any intelligent device with a network communication function. As shown in fig. 1, the face recognition method may include the following steps:
s101, receiving a request for starting a face recognition function, which is sent by a user through client equipment; wherein, the request for starting the face recognition function carries the identification of the current application program.
In this step, the cloud device may receive a request for starting a face recognition function, which is sent by a user through the client device; wherein, the request for starting the face recognition function carries the identification of the current application program. The cloud device in the embodiment of the application can be a cloud mobile phone. The cloud mobile phone is based on an end-cloud integrated virtualization technology, flexibly adapts to individual requirements of users through the digitization capabilities of a cloud network, safety, AI and the like, releases hardware resources of the mobile phone, and loads mobile phone forms applied to massive clouds as required. The cloud mobile phone is based on the 5G network, so that complex calculation and high-capacity data can be stored on the cloud end. The user can see through the long-range real-time control cloud cell-phone of mode of video stream, finally realizes the high in the clouds operation of tall and erect native application of ann and hand trip. The current application in the embodiment of the present application refers to an application in the client device that is providing a face recognition function for a user. The application may be any application installed in the client device that can provide face recognition functionality, such as QQ, WeChat, and so on.
And S102, sending equipment information which is provided by the cloud equipment for realizing the face recognition function to the client equipment according to the identification of the current application program.
In this step, the cloud device may send, to the client device, device information that the cloud device has to implement the face recognition function, according to the identifier of the current application program. Specifically, the cloud device may send at least one screen brightness information of the cloud device to the client device within a preset time length; or sending resolution information of a camera of the cloud equipment to the client equipment when a request for starting the face recognition function is received. The device information in the embodiment of the application may be screen brightness information of the cloud device, and may also be resolution information of a camera of the cloud device.
S103, receiving video stream data of the user acquired by the client device based on the device information.
In this step, the cloud device may receive video stream data of the user acquired by the client device based on the device information. Specifically, the cloud device may receive video stream data of a user, which is acquired by the client device based on screen brightness information of the cloud device, and may also receive video stream data of the user, which is acquired by the client device based on resolution information of a camera of the cloud device.
And S104, carrying out face recognition on the user based on the video stream data of the user.
In this step, the cloud device may perform face recognition on the user based on the video stream data of the user. Specifically, the face recognition system mainly includes four components: the method comprises the steps of face image acquisition and detection, face image preprocessing, face image feature extraction, matching and identification. Acquiring a face image: different face images can be collected through the camera lens, and for example, static images, dynamic images, different positions, different expressions and the like can be well collected. When the user is in the shooting range of the acquisition equipment, the acquisition equipment can automatically search and shoot the face image of the user. Further, face detection: in practice, face detection is mainly used for preprocessing of face recognition, namely, the position and size of a face are accurately calibrated in an image. The face image contains abundant pattern features, such as histogram features, color features, template features, structural features, and the like. The face detection is to extract the useful information and to use the features to realize the face detection. Preprocessing a face image: the image preprocessing for the human face is a process of processing the image based on the human face detection result and finally serving for feature extraction. The original image acquired by the system is limited by various conditions and random interference, so that the original image cannot be directly used, and the original image needs to be subjected to image preprocessing such as gray scale correction, noise filtering and the like in the early stage of image processing. For the face image, the preprocessing process mainly includes light compensation, gray level transformation, histogram equalization, normalization, geometric correction, filtering, sharpening, and the like of the face image. Extracting the features of the face image: features that can be used by a face recognition system are generally classified into visual features, pixel statistical features, face image transform coefficient features, face image algebraic features, and the like. The face feature extraction is performed on some features of the face. Face feature extraction, also known as face characterization, is a process of feature modeling for a face. Matching and identifying the face image: and searching and matching the extracted feature data of the face image with a feature template stored in a database, and outputting a result obtained by matching when the similarity exceeds a threshold value by setting the threshold value. The face recognition is to compare the face features to be recognized with the obtained face feature template, and judge the identity information of the face according to the similarity degree.
The face recognition method provided by the embodiment of the application comprises the steps of firstly receiving a request for starting a face recognition function, which is sent by a user through client equipment; then, according to the identification of the current application program, equipment information which is possessed by the cloud equipment for realizing the face recognition function is sent to the client equipment; then receiving video stream data of a user acquired by the client device based on the device information; and finally, carrying out face recognition on the user based on the video stream data of the user. That is to say, this application can realize the equipment information that face identification function possesses with high in the clouds equipment and send for client equipment gathers user's video stream data based on the equipment information of high in the clouds equipment, because the equipment information of high in the clouds equipment and client equipment is unanimous, just so can not produce the condition of video stretch or other deformations. In the existing face recognition method, the user mobile phones collect the device information based on themselves, the device information of different user mobile phones is different, and the situation of video stretching or other deformation may occur when the device information is sent to the cloud device, so that the face recognition accuracy is very low. The technical scheme provided by the application can greatly improve the success rate of face recognition, and the technical scheme can greatly improve the success rate of face recognition; moreover, the technical scheme of the embodiment of the application is simple and convenient to implement, convenient to popularize and wide in application range.
Example two
Fig. 2 is a second flow chart of the face recognition method according to the embodiment of the present application. Further optimization and expansion are performed based on the technical scheme, and the method can be combined with the various optional embodiments. As shown in fig. 2, the face recognition method may include the following steps:
s201, receiving a request for starting a face recognition function sent by a user through client equipment; wherein, the request for starting the face recognition function carries the identification of the current application program.
S202, sending at least one screen brightness information of the cloud device to the client device within a preset time length according to the identification of the current application program; or sending resolution information of a camera of the cloud equipment to the client equipment when a request for starting the face recognition function is received.
In this step, the cloud device may send at least one screen brightness information of the cloud device to the client device within a preset duration according to the identifier of the current application program; or sending resolution information of a camera of the cloud equipment to the client equipment when a request for starting the face recognition function is received. For example, assuming that the application currently used by the user is QQ, the cloud device may first obtain screen brightness information corresponding to QQ and resolution information of the camera, and then send the screen brightness information corresponding to QQ to the client device within a preset time period; or sending resolution information of a camera corresponding to the QQ to the client device when receiving a request for starting the face recognition function.
Specifically, when the cloud device sends the screen brightness information of the cloud device to the client device, a first time point within a preset time duration may be used as a current time point; then, sending screen brightness information of the cloud equipment at the current time point to the client equipment at the current time point; and then taking the next time point of the current time point as the current time point, and repeatedly executing the operation of sending the screen brightness information of the cloud equipment on the current time point to the client equipment on the current time point until the current time point is the last time point in the preset time length.
S203, receiving video stream data of a user, acquired by the client device based on at least one screen brightness information of the cloud device or resolution information of a camera of the cloud device.
It should be noted that the client device may acquire the video stream data of the user only based on the screen brightness information of the cloud device, may also acquire the video stream data of the user only based on the resolution information of the camera of the cloud device, and may also acquire the video stream data of the user based on the screen brightness information of the cloud device and the resolution information of the camera at the same time.
And S204, carrying out face recognition on the user based on the video stream data of the user.
The face recognition method provided by the embodiment of the application comprises the steps of firstly receiving a request for starting a face recognition function, which is sent by a user through client equipment; then, according to the identification of the current application program, equipment information which is possessed by the cloud equipment for realizing the face recognition function is sent to the client equipment; then receiving video stream data of a user acquired by the client device based on the device information; and finally, carrying out face recognition on the user based on the video stream data of the user. That is to say, this application can realize the equipment information that face identification function possesses with high in the clouds equipment and send for client equipment gathers user's video stream data based on the equipment information of high in the clouds equipment, because the equipment information of high in the clouds equipment and client equipment is unanimous, just so can not produce the condition of video stretch or other deformations. In the existing face recognition method, the user mobile phones collect the device information based on themselves, the device information of different user mobile phones is different, and the situation of video stretching or other deformation may occur when the device information is sent to the cloud device, so that the face recognition accuracy is very low. The technical scheme provided by the application can greatly improve the success rate of face recognition, and the technical scheme can greatly improve the success rate of face recognition; moreover, the technical scheme of the embodiment of the application is simple and convenient to implement, convenient to popularize and wide in application range.
EXAMPLE III
Fig. 3 is a third flowchart of a face recognition method provided in an embodiment of the present application, where the method may be executed by a client device, where the client device may be implemented by software and/or hardware, and the client device may be integrated in any intelligent device with a network communication function. As shown in fig. 3, the face recognition method may include the following steps:
s301, receiving a face recognition instruction sent by a user through a current application program.
In this step, the client device may receive a face recognition instruction sent by the user through the current application program. The client device in the embodiment of the application can be a mobile phone of a user, and can also be other electronic devices used by the user. When a user clicks a button of one application program on the mobile phone, the application program can be triggered to start a face recognition function; at this time, the client device may receive a face recognition instruction sent by the user through the current application program.
S302, responding to a face recognition instruction, and sending a request for starting a face recognition function to the cloud equipment; wherein, the request for starting the face recognition function carries the identification of the current application program.
In this step, the cloud device may send a request for starting a face recognition function to the cloud device in response to the face recognition instruction; wherein, the request for starting the face recognition function carries the identification of the current application program. Specifically, the identifier of the application may be the name of the application, or may be other unique identifier. Different application programs correspond to different identifications, and the purpose of sending the identification of the current application program to the cloud end equipment by the client end equipment is to inform the cloud end equipment of which application program a user is using at the moment, so that the cloud end equipment can acquire screen brightness information corresponding to the application program and resolution information of a camera.
And S303, receiving equipment information which is sent by the cloud equipment and has the face recognition function.
In this step, the client device may receive device information that the cloud device realizes the face recognition function and is sent by the cloud device. The device information in the embodiment of the application can be screen brightness information of the cloud device and resolution information of the camera. Optionally, the client device may receive only screen brightness information of the cloud device, or only resolution information of a camera of the cloud device. In order to improve the accuracy of face recognition, the client device can also receive the screen brightness information of the cloud device and the resolution information of the camera at the same time.
S304, collecting video stream data of a user based on the equipment information; and sending the video stream data of the user to the cloud end equipment, so that the cloud end equipment carries out face recognition on the user based on the video stream data of the user.
In this step, the client device may collect video stream data of the user based on the device information; and sending the video stream data of the user to the cloud end equipment, so that the cloud end equipment carries out face recognition on the user based on the video stream data of the user. Specifically, the client device may acquire video stream data of the user based on screen brightness information of the cloud device and resolution information of the camera; and then sending the collected video stream data to the cloud equipment.
The face recognition method provided by the embodiment of the application comprises the steps of firstly receiving a request for starting a face recognition function, which is sent by a user through client equipment; then, according to the identification of the current application program, equipment information which is possessed by the cloud equipment for realizing the face recognition function is sent to the client equipment; then receiving video stream data of a user acquired by the client device based on the device information; and finally, carrying out face recognition on the user based on the video stream data of the user. That is to say, this application can realize the equipment information that face identification function possesses with high in the clouds equipment and send for client equipment gathers user's video stream data based on the equipment information of high in the clouds equipment, because the equipment information of high in the clouds equipment and client equipment is unanimous, just so can not produce the condition of video stretch or other deformations. In the existing face recognition method, the user mobile phones collect the device information based on themselves, the device information of different user mobile phones is different, and the situation of video stretching or other deformation may occur when the device information is sent to the cloud device, so that the face recognition accuracy is very low. The technical scheme provided by the application can greatly improve the success rate of face recognition, and the technical scheme can greatly improve the success rate of face recognition; moreover, the technical scheme of the embodiment of the application is simple and convenient to implement, convenient to popularize and wide in application range.
Example four
Fig. 4 is a fourth flowchart illustrating a face recognition method according to an embodiment of the present application. Further optimization and expansion are performed based on the technical scheme, and the method can be combined with the various optional embodiments. As shown in fig. 4, the face recognition method may include the following steps:
s401, receiving a face recognition instruction sent by a user through a current application program.
S402, responding to the face recognition instruction, and sending a request for starting a face recognition function to the cloud equipment; wherein, the request for starting the face recognition function carries the identification of the current application program.
S403, receiving at least one screen brightness information of the cloud equipment sent by the cloud equipment within a preset time length; or receiving resolution information of a camera of the cloud device, which is sent by the cloud device when the cloud device receives a request for starting a face recognition function.
In this step, the client device may receive at least one screen brightness information of the cloud device sent by the cloud device within a preset time period; or receiving resolution information of a camera of the cloud device, which is sent by the cloud device when the cloud device receives a request for starting a face recognition function. Specifically, the client device may use a first time point within a preset duration as a current time point; then, receiving screen brightness information of the cloud equipment at the current time point, which is sent by the cloud equipment, at the current time point; and then taking the next time point of the current time point as the current time point, and repeatedly executing the operation of receiving the screen brightness information of the cloud end equipment on the current time point, which is sent by the cloud end equipment, at the current time point until the current time point is the last time point in the preset time length.
S404, acquiring video stream data of a user based on screen brightness information of cloud equipment or resolution information of a camera; and sending the video stream data of the user to the cloud end equipment, so that the cloud end equipment carries out face recognition on the user based on the video stream data of the user.
In this step, the client device may acquire video stream data of the user based on screen brightness information of the cloud device or resolution information of the camera; and sending the video stream data of the user to the cloud end equipment, so that the cloud end equipment carries out face recognition on the user based on the video stream data of the user. Specifically, the client device may use a first time point within a preset duration as a current time point; then replacing the screen brightness information of the client equipment with the screen brightness information of the cloud equipment at the current time point; then, acquiring video stream data of a user based on screen brightness information of the cloud equipment; and taking the next time point of the current time point as the current time point, and repeatedly executing the operation of replacing the screen brightness information of the client device with the screen brightness information of the cloud device at the current time point until the current time point is the last time point in the preset time length. In addition, the client device can replace the resolution information of the camera of the client device with the resolution information of the camera of the cloud device; and acquiring video stream data of a user based on resolution information of a camera of the cloud equipment.
The face recognition method provided by the embodiment of the application comprises the steps of firstly receiving a request for starting a face recognition function, which is sent by a user through client equipment; then, according to the identification of the current application program, equipment information which is possessed by the cloud equipment for realizing the face recognition function is sent to the client equipment; then receiving video stream data of a user acquired by the client device based on the device information; and finally, carrying out face recognition on the user based on the video stream data of the user. That is to say, this application can realize the equipment information that face identification function possesses with high in the clouds equipment and send for client equipment gathers user's video stream data based on the equipment information of high in the clouds equipment, because the equipment information of high in the clouds equipment and client equipment is unanimous, just so can not produce the condition of video stretch or other deformations. In the existing face recognition method, the user mobile phones collect the device information based on themselves, the device information of different user mobile phones is different, and the situation of video stretching or other deformation may occur when the device information is sent to the cloud device, so that the face recognition accuracy is very low. The technical scheme provided by the application can greatly improve the success rate of face recognition, and the technical scheme can greatly improve the success rate of face recognition; moreover, the technical scheme of the embodiment of the application is simple and convenient to implement, convenient to popularize and wide in application range.
EXAMPLE five
Fig. 5 is a schematic structural diagram of a cloud device provided in an embodiment of the present application. As shown in fig. 5, the cloud device 500 includes: a first receiving module 501, a first sending module 502 and a face recognition module 503; wherein the content of the first and second substances,
the first receiving module 501 is configured to receive a request for starting a face recognition function, where the request is sent by a user through a client device; wherein, the request for starting the face recognition function carries the identifier of the current application program;
the first sending module 502 is configured to send, to the client device, device information that the cloud device has the face recognition function according to the identifier of the current application program;
the first receiving module 501 is further configured to receive video stream data of the user, which is acquired by the client device based on the device information;
the face recognition module 503 is configured to perform face recognition on the user based on the video stream data of the user.
Further, the first sending module 502 is specifically configured to send at least one screen brightness information of the cloud device to the client device within a preset time duration; or sending resolution information of a camera of the cloud device to the client device when the request for starting the face recognition function is received.
Further, the first sending module 502 is specifically configured to use a first time point within the preset time period as a current time point; sending screen brightness information of the cloud device at the current time point to the client device at the current time point; and taking the next time point of the current time point as the current time point, and repeatedly executing the operation of sending the screen brightness information of the cloud end equipment on the current time point to the client end equipment on the current time point until the current time point is the last time point in the preset time length.
The cloud device can execute the methods provided by the first embodiment and the second embodiment of the application, and has the corresponding functional modules and beneficial effects of the execution method. For details of the technology that are not described in detail in this embodiment, reference may be made to the face recognition methods provided in the first and second embodiments of the present application.
EXAMPLE six
Fig. 6 is a schematic structural diagram of a client device according to an embodiment of the present application. As shown in fig. 6, the client device 600 includes: a second receiving module 601, a second sending module 602 and a video capturing module 603; wherein the content of the first and second substances,
the second receiving module 601 is configured to receive a face recognition instruction sent by a user through a current application program;
the second sending module 602 is configured to send, to a cloud device, a request for starting a face recognition function in response to the face recognition instruction; wherein, the request for starting the face recognition function carries the identifier of the current application program;
the second receiving module 601 is further configured to receive device information, which is sent by the cloud device and is possessed by the cloud device for implementing the face recognition function;
the video acquisition module is used for acquiring video stream data of the user based on the equipment information; and sending the video stream data of the user to the cloud end equipment, so that the cloud end equipment carries out face recognition on the user based on the video stream data of the user.
Further, the second receiving module 601 is specifically configured to receive at least one screen brightness information of the cloud device sent by the cloud device within a preset time period; or receiving resolution information of a camera of the cloud device, which is sent by the cloud device when the cloud device receives the request for starting the face recognition function.
Further, the second receiving module 601 is specifically configured to use a first time point within the preset time length as a current time point; receiving screen brightness information of the cloud equipment at the current time point, which is sent by the cloud equipment, at the current time point; and taking the next time point of the current time point as the current time point, and repeatedly executing the operation of receiving the screen brightness information of the cloud end equipment on the current time point, which is sent by the cloud end equipment, on the current time point until the current time point is the last time point in the preset time length.
Further, the video capture module 603 is specifically configured to use a first time point within the preset duration as a current time point; replacing the screen brightness information of the client device with the screen brightness information of the cloud device at the current time point; acquiring video stream data of the user based on screen brightness information of the cloud equipment; and taking the next time point of the current time point as the current time point, and repeatedly executing the operation of replacing the screen brightness information of the client device with the screen brightness information of the cloud device at the current time point until the current time point is the last time point in the preset time length.
Further, the video acquisition module 603 is specifically configured to replace resolution information of a camera of the client device with resolution information of a camera of the cloud device; and acquiring video stream data of the user based on resolution information of a camera of the cloud equipment.
The client device can execute the methods provided by the third embodiment and the fourth embodiment of the application, and has the corresponding functional modules and beneficial effects of the execution methods. For details of the technology that are not described in detail in this embodiment, reference may be made to the face recognition methods provided in the third and fourth embodiments of the present application.
In the technical scheme of the disclosure, the acquisition, storage, application and the like of the personal information of the related user all accord with the regulations of related laws and regulations, and do not violate the good customs of the public order.
EXAMPLE seven
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
FIG. 7 illustrates a schematic block diagram of an example electronic device 700 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 7, the device 700 comprises a computing unit 701, which may perform various suitable actions and processes according to a computer program stored in a Read Only Memory (ROM)702 or a computer program loaded from a storage unit 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other by a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
Various components in the device 700 are connected to the I/O interface 705, including: an input unit 706 such as a keyboard, a mouse, or the like; an output unit 707 such as various types of displays, speakers, and the like; a storage unit 708 such as a magnetic disk, optical disk, or the like; and a communication unit 709 such as a network card, modem, wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (19)
1. A face recognition method is applied to cloud equipment, and the method comprises the following steps:
receiving a request for starting a face recognition function sent by a user through client equipment; wherein, the request for starting the face recognition function carries the identifier of the current application program;
according to the identification of the current application program, sending equipment information which is possessed by the cloud equipment for realizing the face recognition function to the client equipment;
receiving video stream data of the user acquired by the client device based on the device information;
and carrying out face recognition on the user based on the video stream data of the user.
2. The method of claim 1, wherein the sending, to the client device, device information with which the cloud device implements the face recognition function comprises:
sending at least one screen brightness information of the cloud device to the client device within a preset time length; or sending resolution information of a camera of the cloud device to the client device when the request for starting the face recognition function is received.
3. The method of claim 2, wherein the sending, to the client device, at least one piece of screen brightness information of the cloud device within a preset time duration comprises:
taking the first time point in the preset time length as the current time point;
sending screen brightness information of the cloud device at the current time point to the client device at the current time point;
and taking the next time point of the current time point as the current time point, and repeatedly executing the operation of sending the screen brightness information of the cloud end equipment on the current time point to the client end equipment on the current time point until the current time point is the last time point in the preset time length.
4. A face recognition method is applied to client equipment and comprises the following steps:
receiving a face recognition instruction sent by a user through a current application program;
responding to the face recognition instruction and sending a request for starting a face recognition function to the cloud end equipment; wherein, the request for starting the face recognition function carries the identifier of the current application program;
receiving device information which is sent by the cloud device and is possessed by the cloud device for realizing the face recognition function;
collecting video stream data of the user based on the device information; and sending the video stream data of the user to the cloud end equipment, so that the cloud end equipment carries out face recognition on the user based on the video stream data of the user.
5. The method of claim 4, wherein the receiving device information sent by the cloud device and provided for the cloud device to implement the face recognition function comprises:
receiving at least one screen brightness information of the cloud equipment, which is sent by the cloud equipment within a preset time length; or receiving resolution information of a camera of the cloud device, which is sent by the cloud device when the cloud device receives the request for starting the face recognition function.
6. The method of claim 5, wherein the receiving at least one piece of screen brightness information of the cloud device sent by the cloud device within a preset time period comprises:
taking the first time point in the preset time length as the current time point;
receiving screen brightness information of the cloud equipment at the current time point, which is sent by the cloud equipment, at the current time point;
and taking the next time point of the current time point as the current time point, and repeatedly executing the operation of receiving the screen brightness information of the cloud end equipment on the current time point, which is sent by the cloud end equipment, on the current time point until the current time point is the last time point in the preset time length.
7. The method of claim 5, wherein said capturing video stream data of the user based on the device information comprises:
taking the first time point in the preset time length as the current time point;
replacing the screen brightness information of the client device with the screen brightness information of the cloud device at the current time point; acquiring video stream data of the user based on screen brightness information of the cloud equipment;
and taking the next time point of the current time point as the current time point, and repeatedly executing the operation of replacing the screen brightness information of the client device with the screen brightness information of the cloud device at the current time point until the current time point is the last time point in the preset time length.
8. The method of claim 5, wherein said capturing video stream data of the user based on the device information comprises:
replacing the resolution information of the camera of the client device with the resolution information of the camera of the cloud device; and acquiring video stream data of the user based on resolution information of a camera of the cloud equipment.
9. A cloud device, the cloud device comprising: the system comprises a first receiving module, a first sending module and a face recognition module; wherein the content of the first and second substances,
the first receiving module is used for receiving a request for starting a face recognition function, which is sent by a user through client equipment; wherein, the request for starting the face recognition function carries the identifier of the current application program;
the first sending module is configured to send, to the client device, device information that the cloud device has the face recognition function according to the identifier of the current application program;
the first receiving module is further configured to receive video stream data of the user, which is acquired by the client device based on the device information;
the face recognition module is used for carrying out face recognition on the user based on the video stream data of the user.
10. The cloud device of claim 9, wherein the first sending module is specifically configured to send at least one screen brightness information of the cloud device to the client device within a preset time duration; or sending resolution information of a camera of the cloud device to the client device when the request for starting the face recognition function is received.
11. The cloud device of claim 10, wherein the first sending module is specifically configured to use a first time point within the preset duration as a current time point; sending screen brightness information of the cloud device at the current time point to the client device at the current time point; and taking the next time point of the current time point as the current time point, and repeatedly executing the operation of sending the screen brightness information of the cloud end equipment on the current time point to the client end equipment on the current time point until the current time point is the last time point in the preset time length.
12. A client device, the client device comprising: the second receiving module, the second sending module and the video acquisition module; wherein the content of the first and second substances,
the second receiving module is used for receiving a face recognition instruction sent by a user through a current application program;
the second sending module is used for responding to the face recognition instruction and sending a request for starting a face recognition function to the cloud end equipment; wherein, the request for starting the face recognition function carries the identifier of the current application program;
the second receiving module is further configured to receive device information, which is sent by the cloud device and is possessed by the cloud device for implementing the face recognition function;
the video acquisition module is used for acquiring video stream data of the user based on the equipment information; and sending the video stream data of the user to the cloud end equipment, so that the cloud end equipment carries out face recognition on the user based on the video stream data of the user.
13. The client device according to claim 12, wherein the second receiving module is specifically configured to receive at least one screen brightness information of the cloud device sent by the cloud device within a preset time period; or receiving resolution information of a camera of the cloud device, which is sent by the cloud device when the cloud device receives the request for starting the face recognition function.
14. The client device according to claim 13, wherein the second receiving module is specifically configured to use a first time point within the preset duration as a current time point; receiving screen brightness information of the cloud equipment at the current time point, which is sent by the cloud equipment, at the current time point; and taking the next time point of the current time point as the current time point, and repeatedly executing the operation of receiving the screen brightness information of the cloud end equipment on the current time point, which is sent by the cloud end equipment, on the current time point until the current time point is the last time point in the preset time length.
15. The client device according to claim 13, wherein the video capture module is specifically configured to use a first time point within the preset duration as a current time point; replacing the screen brightness information of the client device with the screen brightness information of the cloud device at the current time point; acquiring video stream data of the user based on screen brightness information of the cloud equipment; and taking the next time point of the current time point as the current time point, and repeatedly executing the operation of replacing the screen brightness information of the client device with the screen brightness information of the cloud device at the current time point until the current time point is the last time point in the preset time length.
16. The client device of claim 13, wherein the video capture module is specifically configured to replace resolution information of a camera of the client device with resolution information of a camera of the cloud device; and acquiring video stream data of the user based on resolution information of a camera of the cloud equipment.
17. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-3 or 4-8.
18. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any of claims 1-3 or 4-8.
19. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-3 or 4-8.
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