CN111585765A - Face recognition method and device and related equipment - Google Patents
Face recognition method and device and related equipment Download PDFInfo
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Abstract
The application discloses a face recognition method, which comprises the steps of carrying out face acquisition according to a recognition request to obtain face information; identifying the face information through local face data, and judging whether the identification is passed; if the identification is passed, outputting a pass prompt; if the recognition fails, recognizing the face information through the cloud face data, and outputting a pass prompt when the recognition passes; the face recognition method can effectively improve the face recognition efficiency and ensure the user experience. The application also discloses a face recognition device, a face recognition system, face recognition equipment and a computer readable storage medium, which have the beneficial effects.
Description
Technical Field
The present application relates to the field of image processing technologies, and in particular, to a face recognition method, and further, to a face recognition apparatus, a face recognition system, a face recognition device, and a computer-readable storage medium.
Background
In the user identification of the vehicle-mounted system, a face recognition technology is generally used, and a personalized cabin environment can be established for the user through the face recognition. However, due to the requirement of a big data scene, the current information identification is realized through a cloud, namely, the big data stored by the cloud is used for identifying the information to be identified; however, cloud-based big data identification needs to be performed under a networking condition, the identification speed is relatively slow, and therefore, the application scenarios of the face identification of the existing vehicle-mounted system are limited, the identification efficiency is low, and poor experience is brought to users.
Therefore, how to more effectively improve the face recognition efficiency and ensure the user experience is a problem to be solved urgently by the technical staff in the field.
Disclosure of Invention
The method for recognizing the face aims to provide a face recognition method, and the face recognition method can effectively improve face recognition efficiency and ensure user experience; another object of the present application is to provide a face recognition device, a face recognition system, a face recognition apparatus, and a computer-readable storage medium, all of which have the above advantages.
In order to solve the technical problem, the present application provides a face recognition method, including:
acquiring a face according to the identification request to obtain face information;
identifying the face information through local face data, and judging whether the identification is passed;
if the identification is passed, outputting a pass prompt;
and if the identification is not passed, identifying the face information through the cloud face data, and outputting the passing prompt when the identification is passed.
Preferably, the recognizing the face information by the local face data includes:
decrypting the local face data to obtain decrypted local face data;
and identifying the face information through the decrypted local face data.
Preferably, the recognizing the face information through the cloud face data includes:
judging whether the network is in a networking state at present;
if the terminal is in the networking state, the cloud terminal face data are called from a cloud server to identify the face information;
and if the network is not in the networking state, outputting a networking prompt.
Preferably, the face recognition method further includes:
and if the cloud face data fails to identify the face information, outputting a registration prompt.
Preferably, the face recognition method further includes:
acquiring and storing the local face data issued by the cloud server; and the local face data is obtained by screening the cloud server from the cloud face data according to a preset screening strategy.
Preferably, the face recognition method further includes:
and when the face information passes the identification, the face information is synchronously updated to a cloud server.
In order to solve the above technical problem, the present application further provides a face recognition apparatus, including:
the information acquisition module is used for acquiring the face according to the identification request to obtain face information;
the local identification module is used for identifying the face information through local face data and judging whether the identification is passed or not;
the prompt output module is used for outputting a pass prompt if the identification passes;
and the cloud identification module is used for identifying the face information through the cloud face data if the face information is not identified, and outputting the pass prompt when the face information is identified.
Preferably, the local identification module is specifically configured to decrypt the local face data to obtain decrypted local face data; and identifying the face information through the decrypted local face data, and judging whether the identification is passed or not.
Preferably, the cloud identification module is specifically configured to determine whether the local face data is in a networking state at present if the local face data fails to identify the face information; if the mobile terminal is in the networking state, the cloud face data are called from a cloud server to identify the face information, and when the face information passes the identification, the passing prompt is output; and if the network is not in the networking state, outputting a networking prompt.
Preferably, the face recognition device further includes a registration prompt module, configured to output a registration prompt if the cloud face data fails to identify the face information.
Preferably, the face recognition device further includes a local data acquisition module, configured to acquire and store the local face data issued by the cloud server; and the local face data is obtained by screening the cloud server from the cloud face data according to a preset screening strategy.
Preferably, the face recognition device further comprises a cloud data updating module, configured to update the face information to a cloud server synchronously when the face information passes the face information identification.
In order to solve the above technical problem, the present application further provides a face recognition system, which includes:
the local equipment is used for acquiring the face according to the identification request to obtain face information; identifying the face information through local face data, and judging whether the identification is passed; if the identification is passed, outputting a pass prompt; if the recognition fails, recognizing the face information through the cloud face data, and outputting a pass prompt when the recognition passes;
and the cloud server is used for storing the cloud face data.
Preferably, the local device is specifically configured to perform face acquisition according to the identification request to obtain face information; carrying out decryption processing on the local face data to obtain decrypted local face data; identifying the face information through the decrypted local face data, and judging whether the identification is passed; if the identification is passed, outputting a pass prompt; and if the identification is not passed, identifying the face information through the cloud face data, and outputting the passing prompt when the identification is passed.
Preferably, the local device is specifically configured to perform face acquisition according to the identification request to obtain face information; identifying the face information through local face data, and judging whether the identification is passed; if the identification is passed, outputting a pass prompt; if the identification is not passed, judging whether the network is in a networking state at present; if the mobile terminal is in the networking state, the cloud face data are called from a cloud server to identify the face information, and when the face information passes the identification, the passing prompt is output; and if the network is not in the networking state, outputting a networking prompt.
Preferably, the local device is further configured to output a registration prompt if the cloud face data fails to identify the face information.
Preferably, the local device is further configured to acquire and store the local face data sent by the cloud server; and the local face data is obtained by screening the cloud server from the cloud face data according to a preset screening strategy.
Preferably, the local device is further configured to update the face information to a cloud server synchronously when the face information passes the face information identification.
In order to solve the above technical problem, the present application further provides a face recognition device, including:
a memory for storing a computer program;
a processor for implementing the following steps when executing the computer program:
acquiring a face according to the identification request to obtain face information; identifying the face information through local face data, and judging whether the identification is passed; if the identification is passed, outputting a pass prompt; and if the identification is not passed, identifying the face information through the cloud face data, and outputting the passing prompt when the identification is passed.
Preferably, when the processor executes the computer subprogram stored in the memory, the following steps may be specifically implemented: decrypting the local face data to obtain decrypted local face data; and identifying the face information through the decrypted local face data.
Preferably, when the processor executes the computer subprogram stored in the memory, the following steps may be specifically implemented: judging whether the network is in a networking state at present; if the terminal is in the networking state, the cloud terminal face data are called from a cloud server to identify the face information; and if the network is not in the networking state, outputting a networking prompt.
Preferably, when the processor executes the computer program stored in the memory, the following steps may be further implemented: and if the cloud face data fails to identify the face information, outputting a registration prompt.
Preferably, when the processor executes the computer program stored in the memory, the following steps may be further implemented: acquiring and storing the local face data issued by the cloud server; and the local face data is obtained by screening the cloud server from the cloud face data according to a preset screening strategy.
Preferably, when the processor executes the computer program stored in the memory, the following steps may be further implemented: and when the face information passes the identification, the face information is synchronously updated to a cloud server.
To solve the above technical problem, the present application further provides a computer-readable storage medium having a computer program stored thereon, where the computer program, when executed by a processor, implements the following steps:
acquiring a face according to the identification request to obtain face information; identifying the face information through local face data, and judging whether the identification is passed; if the identification is passed, outputting a pass prompt; and if the identification is not passed, identifying the face information through the cloud face data, and outputting the passing prompt when the identification is passed.
Preferably, when executed by a processor, the computer sub-program stored in the computer-readable storage medium may specifically implement the following steps: decrypting the local face data to obtain decrypted local face data; and identifying the face information through the decrypted local face data.
Preferably, when executed by a processor, the computer sub-program stored in the computer-readable storage medium may specifically implement the following steps: judging whether the network is in a networking state at present; if the terminal is in the networking state, the cloud terminal face data are called from a cloud server to identify the face information; and if the network is not in the networking state, outputting a networking prompt.
Preferably, when the computer program stored in the computer readable storage medium is executed by the processor, the following steps can be further implemented: and if the cloud face data fails to identify the face information, outputting a registration prompt.
Preferably, when the computer program stored in the computer readable storage medium is executed by the processor, the following steps can be further implemented: acquiring and storing the local face data issued by the cloud server; and the local face data is obtained by screening the cloud server from the cloud face data according to a preset screening strategy.
Preferably, when the computer program stored in the computer readable storage medium is executed by the processor, the following steps can be further implemented: and when the face information passes the identification, the face information is synchronously updated to a cloud server.
Therefore, according to the technical scheme provided by the application, the local recognition function is added, namely when the face recognition is carried out, the face information to be recognized is recognized by using the data information stored locally, only when the recognition is not passed, the data information stored in the cloud is reused for recognition, and if the local recognition is passed, the cloud big data recognition is not needed, so that the rapid recognition under the network-free environment is realized, the limitation of the network environment is eliminated, the face recognition efficiency is effectively improved, and the user experience is further improved.
The face recognition device, the face recognition system, the face recognition device, the face recognition equipment and the computer readable storage medium have the beneficial effects, and are not repeated herein.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below.
Fig. 1 is a schematic flow chart of a first face recognition method provided in the present application;
fig. 2 is a schematic flow chart of a second face recognition method provided in the present application;
fig. 3 is a schematic flow chart of a third face recognition method provided in the present application;
fig. 4 is a schematic flow chart of a fourth face recognition method provided in the present application;
fig. 5 is a schematic flow chart of a fifth face recognition method provided in the present application;
fig. 6 is a schematic flow chart of a cloud face data updating method provided in the present application;
fig. 7 is a schematic structural diagram of a face recognition apparatus provided in the present application;
fig. 8 is a schematic structural diagram of a face recognition system provided in the present application;
fig. 9 is a schematic structural diagram of a face recognition device provided in the present application.
Detailed Description
The core of the application is to provide a face recognition method, which can effectively improve face recognition efficiency and ensure user experience; another core of the present application is to provide a face recognition apparatus, a face recognition system, a face recognition device, and a computer-readable storage medium, all having the above-mentioned advantages.
In order to make the objects, 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 below with reference to the drawings in the embodiments of the present application.
Referring to fig. 1, fig. 1 is a schematic flow chart of a first face recognition method provided in the present application, where the face recognition method may include:
s101: acquiring a face according to the identification request to obtain face information;
the method aims to realize the acquisition of the face information, and the face information is the face information of the user to be identified. Specifically, when face recognition is required, for example, when a user needs to log in a certain application, an identification request can be initiated based on the front end of the device, and thus, the device master controller can respond to the identification request to perform the identification request on the user to obtain corresponding face information. It can be understood that the face recognition method can be applied to various scenes needing face recognition.
S102: identifying the face information through local face data, and judging whether the identification is passed; if the identification is passed, executing S103; if the identification is not passed, executing S104;
the method comprises the steps of realizing local identification, namely identifying acquired face information by using the local face data, wherein the local face data refers to face information which is stored locally in advance and passes validity verification, can be legal face information acquired during user registration, and can also be face information downloaded from a cloud, and the acquisition mode of the local face data does not influence the implementation of the technical scheme, and the local face data is not limited by the application; certainly, the number of the local face data is not unique, and can be a plurality of face data or one face data, and no matter the number of the local face data is, the local face data can be updated in real time according to actual requirements so as to ensure the accuracy of the identification result. In addition, the present application is also not limited to the specific local storage location and storage form of the local face data.
As a preferred embodiment, the recognizing the face information by the local face data may include: carrying out decryption processing on the local face data to obtain decrypted local face data; and identifying the face information through the decrypted local face data.
The preferred embodiment provides a more specific local identification method, that is, the local face data is decrypted first, and then the decrypted local face data is used to identify the face information to be identified, that is, the local face data is stored locally in an encrypted form, so that the security of the local face data can be effectively ensured, the accuracy of the face identification result is further ensured, the security of the system is further improved, and the login of an illegal user is effectively avoided.
S103: outputting a pass prompt;
the step aims to realize the output through the prompt, namely when the local face recognition passes, the pass prompt can be directly output to remind the user that the recognition passes and the corresponding application or system can be logged in. Therefore, when local face recognition is passed, cloud recognition is not needed through a cloud server, the face recognition process is greatly simplified, and the face recognition efficiency is improved.
S104: identifying the face information through the cloud face data, and judging whether the identification is passed; if the identification is passed, executing S103; if the identification is not passed, executing S105;
the method comprises the steps of identifying the face information acquired by utilizing the cloud face data, wherein the cloud face data is the face information which is stored in a cloud server and passes validity verification, and the data volume is large. Similarly, the cloud face data may also be data updated in real time.
S105: and outputting a failing prompt.
The step aims to realize the output of the failed prompt, namely, when the cloud face identification fails, the failed prompt can be directly output to remind a user that the identification fails, and an identification request can be initiated again to perform face identification.
As a preferred embodiment, the face recognition method may further include: acquiring and storing local face data issued by a cloud server; the local face data are obtained by screening from the cloud face data through the cloud server according to a preset screening strategy.
The preferred embodiment provides a more specific method for acquiring local face data, namely, the local face data is obtained by screening from cloud face data based on a preset screening strategy. It should be noted that the specific content of the preset screening policy is not unique, and for example, the specific content may be obtained by statistics according to login duration corresponding to each cloud-end face data, or obtained by statistics according to login times corresponding to each cloud-end face data, or obtained by statistics according to login time nodes corresponding to each cloud-end face data, such as time nodes in the near term, and the local face data may be screened, which is not limited in the present application.
The face recognition method provided by the application is additionally provided with a local recognition function, namely when face recognition is carried out, the face information to be recognized is firstly recognized by utilizing the data information stored locally, only when recognition is not passed, the data information stored in the cloud is reused for recognition, and if the local recognition is passed, cloud big data recognition is not needed, so that quick recognition under a network-free environment is realized, the limitation of a network environment is eliminated, the face recognition efficiency is effectively improved, and the user experience is further improved.
The face recognition method provided by the present application is further described below by another specific embodiment, referring to fig. 2, fig. 2 is a schematic flow diagram of a second face recognition method provided by the present application, and the face recognition method may include:
s201: acquiring a face according to the identification request to obtain face information;
s202: identifying the face information through local face data, and judging whether the identification is passed; if the identification is passed, executing S203, and if the identification is not passed, executing S204;
s203: outputting a pass prompt;
s204: judging whether the network is in a networking state at present; if not, executing S205, if yes, executing S206;
s205: outputting a networking prompt;
s206: calling cloud face data from a cloud server to identify face information, and judging whether the identification is passed; if the identification is passed, executing S203; if the identification is not passed, executing S207;
s207: and outputting a failing prompt.
The preferred embodiment provides a more specific face recognition method, which can realize networking state judgment. Specifically, the precondition of the cloud face recognition is the networking state, so that when the local face recognition fails, whether the current network state is in the networking state or not can be judged, if the current network state is not in the networking state, a networking prompt is sent to remind a user of networking, and if the current network state is in the networking state, the cloud face data can be called from the cloud server to recognize the face information, so that a corresponding recognition result is obtained. Certainly, the above cloud identification method is only one implementation manner provided in the preferred embodiment, and is not unique, and the face information may also be uploaded to a cloud server, and the cloud server performs face identification on the face information by using cloud face data.
For the specific implementation process of the above steps S201 to S203, S206, and S207, reference may be made to the content of the foregoing embodiment, and details are not repeated here.
The face recognition method provided by the present application is further described below by another specific embodiment, referring to fig. 3, where fig. 3 is a schematic flow diagram of a third face recognition method provided by the present application, and the face recognition method may include:
s301: acquiring a face according to the identification request to obtain face information;
s302: identifying the face information through local face data, and judging whether the identification is passed; if the identification is passed, executing S303; if the identification is not passed, executing S304;
s303: outputting a pass prompt;
s304: identifying the face information through the cloud face data, and judging whether the identification is passed; if the identification is passed, executing S303; if the identification is not passed, executing S305;
s305: and outputting a failed prompt and a registration prompt.
The preferred embodiment provides another specific face recognition method, namely, a user who fails in recognition is reminded to legally register. Specifically, when the face recognition based on the local and cloud ends fails, the user is an unregistered illegal user, and at the moment, a registration prompt is output to remind the user to register.
For the specific implementation process of the steps S301 to S304, reference may be made to the content of the foregoing embodiment, which is not described herein again.
The face recognition method provided by the present application is further described below by another specific embodiment, referring to fig. 4, where fig. 4 is a schematic flow diagram of a fourth face recognition method provided by the present application, and the face recognition method may include:
s401: acquiring a face according to the identification request to obtain face information;
s402: identifying the face information through local face data, and judging whether the identification is passed; if the identification is passed, executing S403; if the identification is not passed, executing S404;
s403: outputting a pass prompt;
s404: synchronously updating the face information to a cloud server;
s405: identifying the face information through the cloud face data, and judging whether the identification is passed; if the identification is passed, executing S403; if the identification is not passed, executing S406;
s406: outputting a fail prompt;
the preferred embodiment provides a more specific face recognition method, which can update the cloud face data. Specifically, the face information which has passed through the face recognition can be synchronously updated to the cloud server so as to provide updated legal sample data support for subsequent face recognition, further, the synchronous updating process can be realized by comparing the face data which passes through the recognition with each cloud face data, if the face information has higher similarity or is the same with a certain cloud face data, the face information does not need to be added to the cloud server, the repetition is avoided, and if the similarity is lower, the face information is stored to the cloud server. Similarly, the update of the cloud face data needs to be performed under a networking condition, so that if the cloud face data is not in a networking state at present, the face data passing through the local identification can be stored locally, and the update of the cloud face data is performed when a network connection exists. Further, the update may be performed at regular time intervals.
For the specific implementation of the steps S401 to S403, S405 and S406, reference may be made to the content of the foregoing embodiment, which is not described herein again.
On the basis of the above embodiments, the embodiment of the present application provides a more specific face recognition method, taking face recognition of a vehicle-mounted system as an example.
First, the local device includes a device end and an edge device connected thereto for implementing face recognition. When a new user logs in for the first time, networking registration is needed, and registration information is uploaded to a cloud server to be stored; the registration information may include a user name, a user ID, a user password, and the like. Further, the local device acquires the face data from the cloud server as local face data, specifically, the face data can be pushed by the cloud server, and for the push strategy, a certain number of pieces of face information with the highest use frequency in a period of time, for example, the face information which is used most in 3 days, can be counted, so that the local face recognition hit rate is ensured. From this, local equipment can carry out local face identification earlier when carrying out face identification, both guarantee the recognition efficiency, also need not the networking, only local face identification is out of date, carries out the networking again and realizes high in the clouds face identification.
Secondly, for the cloud server, the cloud server can be used for storing the cloud face data and realizing information statistics, wherein the statistical information includes but is not limited to user login time, user login duration, user login times and the like, then a certain number of face information with the highest use frequency in a period of time are counted, and the face information is synchronized to the local device. Of course, the synchronization process may be real-time synchronization, or may be performed at certain time intervals.
Based on this, please refer to fig. 5, where fig. 5 is a schematic flow chart of a fifth face recognition method provided in the present application, which specifically includes:
step one, a user face logs in and face information is collected;
step two, carrying out local face recognition, judging whether the recognition is passed or not, if so, executing step three, and if not, executing step four;
step three, synchronizing the face information to a cloud server;
step four, judging whether networking is successful, if not, executing step five, and if so, executing step six;
step five, outputting a networking prompt;
step six, carrying out cloud face recognition, judging whether the recognition is passed or not, if so, executing step three, and if not, executing step seven;
and step seven, outputting a registration prompt.
Referring to table 1, table 1 is a local face data storage structure table provided in the present application:
table 1 local face data storage structure table
Further, please refer to fig. 6, and fig. 6 is a schematic flow chart of a cloud face data updating method provided in the present application.
Step one, acquiring recognized face data;
step two, judging whether the recognized face data is Ture, if the recognized face data is Ture, indicating that the recognition is passed, executing step three, if the recognized face data is False, indicating that the recognition is not passed, and ignoring the recognized face data;
step three, judging whether the recognized face data is updated, if so, then not needing to carry out cloud server synchronization, and if not, then executing step four;
and step four, synchronizing the recognized face data to a cloud server.
Therefore, the face recognition method provided by the embodiment adds a local recognition function, that is, when face recognition is performed, the face information to be recognized is firstly recognized by using the data information stored locally, and only when the recognition is not passed, the data information stored in the cloud is reused for recognition, and if the local recognition is passed, cloud big data recognition is not required, so that rapid recognition in a non-network environment is realized, the limitation of a network environment is eliminated, the face recognition efficiency is effectively improved, and the user experience is further improved.
In the following, the face recognition apparatus provided by the embodiment of the present application is introduced, and the face recognition apparatus described below and the face recognition method described above may be referred to correspondingly.
Referring to fig. 7, fig. 7 is a schematic structural diagram of a face recognition apparatus provided in the present application, where the face recognition apparatus may include:
the information acquisition module 1 is used for acquiring a face according to the identification request to obtain face information;
the local identification module 2 is used for identifying the face information through local face data and judging whether the identification is passed or not;
the prompt output module 3 is used for outputting a pass prompt if the identification is passed;
and the cloud identification module 4 is used for identifying the face information through the cloud face data if the identification fails, and outputting a pass prompt when the identification passes.
The application provides a face recognition device adds local recognition function, when carrying out face recognition promptly, at first utilize the data information of local storage to treat the face information of discernment and discern, only when discerning not passing through, the data information of recycling high in the clouds storage discerns, if local discernment passes through, then need not to carry out the big data recognition in high in the clouds, therefore, realized the quick discernment under the no network environment, not only broken away from the restriction of network environment, still effectual face recognition efficiency that has improved, user experience has further been improved.
In some specific embodiments, the local identification module is specifically configured to decrypt the local face data to obtain decrypted local face data; and identifying the face information through the decrypted local face data, and judging whether the identification is passed or not.
In some specific embodiments, the cloud identification module is specifically configured to determine whether the current network is in a connected state if the local face data fails to identify the face information; if the cloud server is in the networking state, cloud face data are called from the cloud server to identify face information, and when the identification is passed, a passing prompt is output; and if the mobile terminal is not in the networking state, outputting a networking prompt.
In some specific embodiments, the face recognition device may further include a registration prompt module, configured to output a registration prompt if the cloud face data fails to identify the face information.
In some specific embodiments, the face recognition device may further include a local data acquisition module, configured to acquire and store local face data sent by the cloud server; the local face data are obtained by screening from the cloud face data through the cloud server according to a preset screening strategy.
In some specific embodiments, the face recognition device may further include a cloud data updating module, configured to update the face information to the cloud server synchronously when the face information passes through the face recognition.
The system provided by the embodiment of the present application is introduced below, and the system described below and the face recognition method described above may be referred to correspondingly.
Referring to fig. 8, fig. 8 is a schematic structural diagram of a face recognition system provided in the present application, where the face recognition system may include:
the local device 10 is configured to perform face acquisition according to the identification request to obtain face information; identifying the face information through local face data, and judging whether the identification is passed; if the identification is passed, outputting a pass prompt; if the identification is not passed, identifying the face information through the cloud face data, and outputting a pass prompt when the identification is passed;
and the cloud server 20 is used for storing the cloud face data.
In some specific embodiments, the local device 10 may be specifically configured to perform face acquisition according to an identification request to obtain face information; carrying out decryption processing on the local face data to obtain decrypted local face data; identifying the face information through the decrypted local face data, and judging whether the identification is passed; if the identification is passed, outputting a pass prompt; and if the identification is not passed, identifying the face information through the cloud face data, and outputting a pass prompt when the identification is passed.
In some specific embodiments, the local device 10 may be specifically configured to perform face acquisition according to an identification request to obtain face information; identifying the face information through local face data, and judging whether the identification is passed; if the identification is passed, outputting a pass prompt; if the identification is not passed, judging whether the network is in a networking state at present; if the cloud server is in the networking state, cloud face data are called from the cloud server to identify face information, and when the identification is passed, a passing prompt is output; and if the mobile terminal is not in the networking state, outputting a networking prompt.
In some specific embodiments, the local device 10 may be further configured to output a registration prompt if the cloud-based face data fails to identify the face information.
In some specific embodiments, the local device 10 may be further configured to obtain and store local face data sent by a cloud server; the local face data are obtained by screening from the cloud face data through the cloud server according to a preset screening strategy.
In some specific embodiments, the local device 10 may further be configured to update the face information to the cloud server synchronously when the face information identification passes.
In the following, the apparatuses provided in the embodiments of the present application are introduced, and the apparatuses described below and the face recognition methods described above may be referred to correspondingly.
Referring to fig. 9, fig. 9 is a schematic structural diagram of a face recognition device provided in the present application, where the face recognition device may include:
a memory 11 for storing a computer program;
the processor 12, when executing the computer program stored in the memory 11, may implement the following steps:
acquiring a face according to the identification request to obtain face information; identifying the face information through local face data, and judging whether the identification is passed; if the identification is passed, outputting a pass prompt; and if the identification is not passed, identifying the face information through the cloud face data, and outputting a pass prompt when the identification is passed.
In some specific embodiments, when the processor 12 executes the computer subprogram stored in the memory 11, the following steps may be specifically implemented: carrying out decryption processing on the local face data to obtain decrypted local face data; and identifying the face information through the decrypted local face data.
In some specific embodiments, when the processor 12 executes the computer subprogram stored in the memory 11, the following steps may be specifically implemented: judging whether the network is in a networking state at present; if the mobile terminal is in the networking state, cloud face data are called from a cloud server to identify face information; and if the mobile terminal is not in the networking state, outputting a networking prompt.
In some specific embodiments, when the processor 12 executes the computer program stored in the memory 11, the following steps can be further implemented: and if the cloud face data fails to identify the face information, outputting a registration prompt.
In some specific embodiments, when the processor 12 executes the computer program stored in the memory 11, the following steps can be further implemented: acquiring and storing local face data issued by a cloud server; the local face data are obtained by screening from the cloud face data through the cloud server according to a preset screening strategy.
In some specific embodiments, when the processor 12 executes the computer program stored in the memory 11, the following steps can be further implemented: and when the face information passes the identification, the face information is synchronously updated to the cloud server.
Further, an embodiment of the present application also discloses a computer-readable storage medium for storing a computer program, where the computer program, when executed by a processor, can implement the following steps:
acquiring a face according to the identification request to obtain face information; identifying the face information through local face data, and judging whether the identification is passed; if the identification is passed, outputting a pass prompt; and if the identification is not passed, identifying the face information through the cloud face data, and outputting a pass prompt when the identification is passed.
In some specific embodiments, when executed by a processor, the computer sub-program stored in the computer-readable storage medium may specifically implement the following steps: carrying out decryption processing on the local face data to obtain decrypted local face data; and identifying the face information through the decrypted local face data.
In some specific embodiments, when executed by a processor, the computer sub-program stored in the computer-readable storage medium may specifically implement the following steps: judging whether the network is in a networking state at present; if the mobile terminal is in the networking state, cloud face data are called from a cloud server to identify face information; and if the mobile terminal is not in the networking state, outputting a networking prompt.
In some specific embodiments, when executed by a processor, a computer program stored in a computer readable storage medium may further implement the steps of: and if the cloud face data fails to identify the face information, outputting a registration prompt.
In some specific embodiments, when executed by a processor, a computer program stored in a computer readable storage medium may further implement the steps of: acquiring and storing local face data issued by a cloud server; the local face data are obtained by screening from the cloud face data through the cloud server according to a preset screening strategy.
In some specific embodiments, when executed by a processor, a computer program stored in a computer readable storage medium may further implement the steps of: and when the face information passes the identification, the face information is synchronously updated to the cloud server.
The computer-readable storage medium may include: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
For a detailed description of the computer-readable storage medium provided in the present application, please refer to the above method embodiments, which are not described herein again.
The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The face recognition method, apparatus, system, device and computer-readable storage medium provided by the present application are described in detail above. The principles and embodiments of the present application are explained herein using specific examples, which are provided only to help understand the method and the core idea of the present application. It should be noted that, for those skilled in the art, it is possible to make several improvements and modifications to the present application without departing from the principle of the present application, and these improvements and modifications also fall into the elements of the protection scope of the claims of the present application.
Claims (10)
1. A face recognition method, comprising:
acquiring a face according to the identification request to obtain face information;
identifying the face information through local face data, and judging whether the identification is passed;
if the identification is passed, outputting a pass prompt;
and if the identification is not passed, identifying the face information through the cloud face data, and outputting the passing prompt when the identification is passed.
2. The method of claim 1, wherein the identifying the face information through local face data comprises:
decrypting the local face data to obtain decrypted local face data;
and identifying the face information through the decrypted local face data.
3. The method of claim 1, wherein the recognizing the face information through cloud face data comprises:
judging whether the network is in a networking state at present;
if the terminal is in the networking state, the cloud terminal face data are called from a cloud server to identify the face information;
and if the network is not in the networking state, outputting a networking prompt.
4. The face recognition method of claim 3, further comprising:
and if the cloud face data fails to identify the face information, outputting a registration prompt.
5. The face recognition method of claim 3, further comprising:
acquiring and storing the local face data issued by the cloud server; and the local face data is obtained by screening the cloud server from the cloud face data according to a preset screening strategy.
6. The face recognition method of any one of claims 1 to 5, further comprising:
and when the face information passes the identification, the face information is synchronously updated to a cloud server.
7. A face recognition apparatus, comprising:
the information acquisition module is used for acquiring the face according to the identification request to obtain face information;
the local identification module is used for identifying the face information through local face data and judging whether the identification is passed or not;
the prompt output module is used for outputting a pass prompt if the identification passes;
and the cloud identification module is used for identifying the face information through the cloud face data if the face information is not identified, and outputting the pass prompt when the face information is identified.
8. A face recognition system, comprising:
the local equipment is used for acquiring the face according to the identification request to obtain face information; identifying the face information through local face data, and judging whether the identification is passed; if the identification is passed, outputting a pass prompt; if the recognition fails, recognizing the face information through the cloud face data, and outputting a pass prompt when the recognition passes;
and the cloud server is used for storing the cloud face data.
9. A face recognition device, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the face recognition method according to any one of claims 1 to 6 when executing the computer program.
10. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by the processor, carries out the steps of the face recognition method according to any one of claims 1 to 6.
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Application publication date: 20200825 |