Face-related data management method and device, medium and electronic equipment

Abstract

Embodiments of the present application provide a face-related data management method and device, a computer readable medium and an electronic device. The method comprises: determining redundant face-related data, the redundant face-related data being face-related data stored on at least two face terminal devices, the face-related data being data used to identify face information; eliminating the redundant face-related data from at least one face terminal device, and continuing to store the redundant face-related data on at least one face terminal device other than the at least one face terminal device. The technical solution provided by the embodiments of the present application can reduce the consumption of storage resources used to store face-related data, ensure the availability of face-related data, and achieve scientific and efficient management of face-related data.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of face recognition, in particular to a face-related data management method and device, a computer readable medium and an electronic device. BACKGROUND

[0002] Currently, when performing face recognition, offline face recognition is mainly achieved by storing face-related data offline in the local terminal. However, in order to achieve good face recognition results, a large amount of face-related data needs to be stored, and thus storing a large amount of face-related data in the local terminal will occupy too much local storage resources, causing waste of storage resources. SUMMARY

[0003] Embodiments of the present application provide a face-related data management method and device, a computer readable medium and an electronic device, thereby reducing the storage resources consumed by storing face-related data in the local terminal to at least some extent.

[0004] Other features and advantages of the present application will become apparent from the following detailed description, or will be learned by practice of the present application.

[0005] According to an aspect of an embodiment of the present application, a face-related data management method is provided, the method comprising: determining redundant face-related data, the redundant face-related data being face-related data stored on at least two face terminal devices, the face-related data being data used to identify face information; eliminating the redundant face-related data from at least one face terminal device, and continuing to store the redundant face-related data on at least one face terminal device other than the at least one face terminal device.

[0006] According to an aspect of an embodiment of the present application, a face-related data management device is provided, the device comprising: a determination unit configured to determine redundant face-related data, the redundant face-related data being face-related data stored on at least two face terminal devices, the face-related data being data used to identify face information; and an elimination unit configured to eliminate the redundant face-related data from at least one face terminal device, and continue to store the redundant face-related data on at least one face terminal device other than the at least one face terminal device.

[0007] In some embodiments of the present application, based on the foregoing scheme, each face terminal device stores face-related data and identity information corresponding to the face-related data, the determination unit is configured to: if, according to the first identity information sent by the first face terminal device other than the current face terminal device, it is determined that the first identity information is stored locally in the current face terminal device, the face-related data corresponding to the first identity information is taken as redundant face-related data; and the elimination unit is configured to: eliminate the redundant face-related data stored locally.

[0008] In some embodiments of the present application, based on the foregoing scheme, the determination unit is configured to: determine redundant face-related data according to face-related data issued to multiple face terminal devices, wherein each face terminal device stores face-related data issued thereto; and the elimination unit is configured to: send an elimination instruction to the at least one face terminal device to eliminate the redundant face-related data from the at least one face terminal device.

[0009] In some embodiments of the present application, based on the foregoing scheme, the elimination unit is configured to: obtain an elimination strategy corresponding to a specified time; according to the current time reaching the specified time, determine a target face terminal device according to the elimination strategy corresponding to the specified time, wherein the target face terminal device is a face terminal device that needs to eliminate redundant face-related data; and send an elimination instruction to the target face terminal device to eliminate the redundant face-related data from the target face terminal device.

[0010] In some embodiments of the present application, based on the foregoing scheme, the determination unit is further configured to: receive face data sent by a face terminal device; and according to the face data matching pre-stored face-related data, send the face-related data and identity information corresponding to the face-related data to the face terminal device.

[0011] In some embodiments of the present application, based on the foregoing scheme, each face terminal device in the plurality of face terminal devices is connected to each other via a network, and the determination unit is configured to: receive face data sent by the face terminal device according to the face data not matching face-related data retrieved.

[0012] In some embodiments of the present application, based on the foregoing scheme, the determination unit is further configured to: according to the face data matching pre-stored face-related data, perform a payment operation on a payment account corresponding to the face-related data.

[0013] In some embodiments of this application, based on the foregoing scheme, the determining unit is further configured to: receive identity identification information sent by a face terminal device, wherein the identity identification information is sent by the face terminal device after acquiring face data based on face-related data retrieved from the plurality of face terminal devices that matches the face data, and the identity identification information corresponds to the retrieved face-related data; and perform a payment operation on the payment account corresponding to the identity identification information.

[0014] In some embodiments of this application, based on the aforementioned scheme, the elimination unit is configured to: determine a second face terminal device based on the frequency with which the payment account corresponding to the redundant face-related data makes payments through each face terminal device, wherein the payment account corresponding to the redundant face-related data among the plurality of face terminal devices makes payments through a third face terminal device more frequently than the second face terminal device; and send an elimination instruction to the second face terminal device to eliminate the redundant face-related data from the second face terminal device.

[0015] In some embodiments of this application, based on the foregoing scheme, the identity information is the search result returned by other face terminal devices besides the face terminal device itself, which is first received by the face terminal device.

[0016] In some embodiments of this application, based on the aforementioned scheme, the network connection between the multiple face terminal devices is a Bluetooth connection.

[0017] In some embodiments of this application, based on the foregoing scheme, the face terminal device has a camera, and the face data is a face photo extracted from face streaming media data collected by the camera.

[0018] According to one aspect of the embodiments of this application, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the face-related data management method as described in the above embodiments.

[0019] According to one aspect of the embodiments of this application, an electronic device is provided, including: one or more processors; and a storage device for storing one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the face-related data management method as described in the above embodiments.

[0020] In some embodiments of this application, redundant face-related data stored simultaneously on multiple face terminal devices is first identified. This redundant data is then removed from at least one face terminal device storing it. This reduces the overall storage resources consumed by each face terminal device, alleviating the problem of rapidly increasing storage space on face terminal devices, improving storage efficiency, and significantly reducing storage costs. Simultaneously, continuing to store the redundant face-related data on at least one face terminal device ensures its availability. Therefore, the technical solutions provided by these embodiments reduce the consumption of storage resources for face-related data while ensuring its availability, achieving scientific and efficient management of face-related data.

[0021] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0022] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:

[0023] Figure 1 A schematic diagram of an exemplary system architecture to which the technical solutions of the embodiments of this application can be applied is shown;

[0024] Figure 2 A schematic diagram of the external appearance of a face terminal device according to an embodiment of this application is shown;

[0025] Figure 3 A flowchart illustrating a method for managing face-related data according to an embodiment of this application is shown;

[0026] Figure 4 An embodiment according to this application is shown. Figure 3 A flowchart detailing the intermediate steps;

[0027] Figure 5 Another embodiment according to this application is shown. Figure 3 A flowchart detailing the intermediate steps;

[0028] Figure 6 A flowchart illustrating the process of removing redundant face-related data according to a removal strategy according to an embodiment of this application is shown.

[0029] Figure 7 A flowchart illustrating the sending of face-related data and identity information to a face recognition terminal device according to an embodiment of this application is shown;

[0030] Figure 8 A flowchart illustrating a face recognition-based payment method according to an embodiment of this application is shown;

[0031] Figure 9 A flowchart illustrating the process of removing redundant face-related data according to an embodiment of this application is shown;

[0032] Figure 10 A block diagram illustrating the overall architecture of the technical solutions that can implement the embodiments of this application is shown;

[0033] Figure 11 A block diagram of a face-related data management device according to an embodiment of this application is shown;

[0034] Figure 12 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown. Detailed Implementation

[0035] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art.

[0036] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0037] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0038] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily need to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0039] Currently, many scenarios require the use of facial recognition, and offline facial recognition is one of the important solutions for achieving facial recognition. As mentioned earlier, in related technologies, the main way to achieve offline facial recognition is by storing facial-related data offline on the terminal's local machine. This requires storing a large amount of facial-related data locally, which consumes excessive local storage resources, has low storage efficiency, and limits the actual storage capacity of facial-related data.

[0040] Therefore, this application first provides a method for managing face-related data. Face-related data is data used for face recognition, carrying facial feature information. Face recognition is a biometric technology that identifies individuals based on their facial features. This technology involves using a camera or webcam to capture images or video streams containing faces, automatically detecting faces in the images, and then performing face recognition on the detected faces. It is also commonly referred to as portrait recognition or facial recognition. The face-related data management method provided in this application can achieve scientific and efficient management of face-related data storage, significantly reducing storage resource consumption.

[0041] Figure 1 A schematic diagram of an exemplary system architecture to which the technical solutions of the embodiments of this application can be applied is shown. For example... Figure 1 As shown, the system architecture may include a local area network (LAN) 100, a network 110, and a cloud server 120. The LAN 100 includes at least a first face recognition terminal device 101, a second face recognition terminal device 102, a third face recognition terminal device 103, a fourth face recognition terminal device 104, and a fifth face recognition terminal device 105. Each face recognition terminal device has a camera capable of collecting facial data. Each face recognition terminal device is used for facial recognition during consumer payment and also has storage capabilities. Any two face recognition terminal devices within the LAN 100 can communicate with each other, and each face recognition terminal device within the LAN 100 can also communicate with the cloud server 120 via the network 110. Figure 1The system architecture shown implements the following process for managing face-related data: First, each face terminal device downloads data from the cloud server 120 via network 110 to obtain face-related data. Therefore, at least one face terminal device in the local area network 100 will store face-related data. The two cloud servers 120 may send the same face-related data to multiple face terminal devices. Next, the cloud server 120 determines redundant face-related data based on the face-related data sent to multiple face terminal devices. Finally, the cloud server 120 sends a removal instruction to at least one face terminal device that stores redundant face-related data to remove the redundant face-related data.

[0042] In some embodiments of this application, after the cloud server 120 sends a removal instruction to the face terminal device and the face terminal device removes redundant face-related data according to the removal instruction, the redundant face-related data will be stored only on one face terminal device.

[0043] In some embodiments of this application, any two face terminal devices in the local area network 100 can communicate to determine whether redundant face-related data is stored on the two face terminal devices, and the redundant face-related data stored on both face terminal devices can be removed from one of the face terminal devices.

[0044] It should be noted that, Figure 1 The example shown is only one embodiment of this application. Although Figure 1 The solution in this embodiment is used in a facial recognition payment scenario, but the facial data management method provided in this application can also be applied to access control and other scenarios where facial recognition can be used; although Figure 1 In this embodiment, the face-related data is downloaded from a cloud server by each face terminal device; however, in other embodiments of this application, the face-related data can be pre-stored on the face terminal device. Figure 1 In this embodiment, the local area network 100 includes five face recognition terminal devices. However, in other embodiments or specific applications of this application, the local area network 100 may include any number of face recognition terminal devices. This application does not limit the scope of protection in any way, nor should it restrict the scope of protection of this application.

[0045] Figure 2 A schematic diagram of the external appearance of a face recognition terminal device according to an embodiment of this application is shown. Please refer to... Figure 2 This facial recognition terminal device is equipped with a camera and a facial recognition payment client, which can be used for facial recognition payments. This facial recognition terminal device is actually a facial recognition Internet of Things (IoT) device. Figure 2The facial recognition terminal devices can be installed in various offline stores, allowing consumers to make payments simply by scanning their faces, without needing to operate their mobile phones, which is convenient and fast.

[0046] It is easy to understand that the face-related data management method provided in this application embodiment can be executed by any type of terminal device. It can be executed by a face terminal device that stores face-related data, or by other devices that can communicate with the face terminal device, such as through a cloud server or a cloud server cluster.

[0047] Therefore, the embodiments of this application can be applied to terminals or servers. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. The terminal and server can be directly or indirectly connected via wired or wireless communication, and this application does not impose any restrictions.

[0048] The face-related data management method provided in this application embodiment can be implemented using cloud computing.

[0049] Cloud computing is a computing model that distributes computing tasks across a large pool of computers, enabling various application systems to access computing power, storage space, and information services as needed. The network providing these resources is called the "cloud." From the user's perspective, resources in the "cloud" appear infinitely scalable, readily available, on-demand, and expandable, with payment based on usage.

[0050] As a provider of fundamental cloud computing capabilities, a cloud resource pool (referred to as a cloud platform, generally called IaaS (Infrastructure as a Service)) platform is established. Various types of virtual resources are deployed in the resource pool for external customers to choose from. The cloud resource pool mainly includes: computing devices (virtualized machines containing operating systems), storage devices, and network devices.

[0051] Based on logical function, a PaaS (Platform as a Service) layer can be deployed on top of the IaaS (Infrastructure as a Service) layer, and a SaaS (Software as a Service) layer can be deployed on top of the PaaS layer. Alternatively, SaaS can be deployed directly on top of IaaS. PaaS is a platform for running software, such as databases and web containers. SaaS refers to various types of business software, such as web portals and bulk SMS senders. Generally speaking, SaaS and PaaS are upper layers compared to IaaS.

[0052] The implementation details of the technical solutions in the embodiments of this application are described in detail below:

[0053] Figure 3 A flowchart illustrating a method for managing face-related data according to an embodiment of this application is shown. This method can be executed by any device with storage and communication capabilities, including locally located smart payment hardware devices and cloud devices such as cloud servers or cloud server clusters. (Refer to...) Figure 3 As shown, the method for managing face-related data includes at least the following steps:

[0054] In step 310, redundant face-related data is determined. The redundant face-related data is face-related data stored on at least two face terminal devices. The face-related data is data used to identify face information.

[0055] Specifically, face-related data can be a face image or photograph that fully records facial information, or it can be facial feature data. Facial feature data contains key feature information of the face, such as the coordinates of key locations on the face, like the eyes and nose. Facial feature data can be extracted from a face photograph.

[0056] The face recognition terminal device can store a client for face recognition, which uses face-related data to perform face recognition.

[0057] Redundant face-related data refers to face-related data stored on at least two face terminal devices, meaning that the redundant face-related data is stored simultaneously on at least two face terminal devices.

[0058] In one embodiment of this application, the local area network includes multiple face terminal devices, and at least two face terminal devices in the local area network store face-related data. Redundant face-related data refers to face-related data stored simultaneously on at least two face terminal devices in the local area network.

[0059] For a local area network (LAN), it will store multiple identical redundant face-related data. As long as any face terminal device in the LAN stores redundant face-related data, the LAN can be used for face recognition. In other words, the face-related data stored by multiple face terminal devices can be used together for face recognition, so redundant face-related data is redundant.

[0060] In step 320, redundant face-related data is removed from at least one face terminal device, and redundant face-related data continues to be stored on at least one face terminal device other than at least one face terminal device.

[0061] It is easy to understand that redundant face-related data can only be removed from a face-recognition terminal device if it stores such data. Therefore, in this step, at least one face-recognition terminal device that performs the redundant face-related data removal operation is one that stores such data.

[0062] If a set of redundant face-related data consists of multiple identical sets of redundant face-related data, and the sets of redundant face-related data are different from each other, then when there are multiple sets of redundant face-related data, this step needs to remove each set of redundant face-related data separately, so that for each set of redundant face-related data, at least one redundant face-related data is retained in at least one face terminal device.

[0063] If there are n face terminal devices in the local area network that store redundant face-related data, then after step 320 removes the redundant face-related data, the maximum number of face terminal devices in the local area network whose redundant face-related data has been removed is n-1, and the minimum number is 1; the maximum number of face terminal devices in the local area network that continue to store redundant face-related data is also n-1, and the minimum number is also 1.

[0064] In one embodiment of this application, storing redundant face-related data on at least one face terminal device other than at least one face terminal device includes: storing redundant face-related data on a single face terminal device.

[0065] In this embodiment of the application, by retaining redundant face-related data only on one face terminal device, the availability of redundant face-related data is ensured while eliminating redundant data to the greatest extent and reducing the consumption of storage resources.

[0066] There are many ways to remove redundant face-related data.

[0067] In one embodiment of this application, removing redundant face-related data from at least one face terminal device includes: periodically removing redundant face-related data from at least one face terminal device.

[0068] It's easy to understand that constantly removing redundant face-related data would not only consume a lot of computing resources, but also reduce the usability of the data due to potential malfunctions in face recognition devices. Therefore, periodically removing redundant face-related data allows it to be retained on multiple face recognition devices simultaneously for a period of time, thereby improving data usability.

[0069] In one embodiment of this application, removing redundant face-related data from at least one face terminal device includes: obtaining the average downtime of the face terminal device storing redundant face-related data; determining the target face terminal device for which redundant face-related data needs to be removed based on the average downtime; and removing the redundant face-related data from the target face terminal device.

[0070] In one embodiment of this application, determining the target face terminal device for redundant face-related data removal based on the average downtime includes: selecting the face terminal device with the highest average downtime as the target face terminal device for redundant face-related data removal.

[0071] In one embodiment of this application, determining the target face terminal device for redundant face-related data removal based on the average downtime includes: selecting other face terminal devices besides the face terminal device with the lowest corresponding average downtime as the target face terminal devices for redundant face-related data removal.

[0072] Other face terminal devices besides the one with the lowest average downtime are considered to have an average downtime that is not the lowest. In this embodiment, redundant face-related data is removed by using the face terminal devices with average downtime that is neither the lowest nor the highest as target face terminal devices. Therefore, the average downtime of face terminal devices that can retain redundant face-related data is relatively low, effectively ensuring the availability of redundant face-related data.

[0073] Figure 4 An embodiment according to this application is shown. Figure 3 A flowchart detailing the steps in the process. Figure 4 In this embodiment, each facial recognition terminal device stores face-related data and corresponding identity information. Please refer to [link to relevant documentation]. Figure 4 Specifically, this may include the following steps:

[0074] In step 310', if it is determined that the first identity information is stored locally on the current face terminal device based on the first identity information sent by the first face terminal device other than the current face terminal device, then the face-related data corresponding to the first identity information is used as redundant face-related data.

[0075] The current face terminal device is the execution subject of this application embodiment, that is, the execution subject of this application embodiment is a face terminal device.

[0076] Identity information can be any type of information that uniquely identifies a person. This includes information such as ID card numbers, mobile phone numbers, bank card numbers, and account numbers, which can be associated with a unique user. It can also be information that uniquely corresponds to ID card numbers, mobile phone numbers, bank card numbers, and account numbers. Facial recognition is the process of determining a person's identity; therefore, storing identity information corresponding to facial data can be used for facial recognition.

[0077] The first face recognition terminal device can send multiple identity identification information to the current face recognition terminal device. For example, it can send all the identity identification information stored in the current face recognition terminal device. For each identity identification information sent by the first face recognition terminal device, the current face recognition terminal device queries the identity identification information stored locally to determine whether the identity identification information is stored locally. If it is determined that the identity identification information is stored locally, the identity identification information can be used as the first identity identification information, and the face-related data corresponding to the first identity identification information can be used as redundant face-related data.

[0078] The first face recognition terminal device is different from the current face recognition terminal device. The same face-related data corresponds to the same identity information, and the same identity information also corresponds to the same face-related data. The first identity information sent by the first face recognition terminal device is the identity information corresponding to the face-related data stored on the first face recognition terminal device. Therefore, if the current face recognition terminal device also stores the first identity information locally, it means that the current face recognition terminal device and the first face recognition terminal device redundantly store the same face-related data, and this face-related data corresponds to the first identity information.

[0079] In step 320', redundant face-related data stored locally will be removed.

[0080] Since it has been confirmed that the redundant face-related data is also stored on the first face recognition terminal device, the redundant face-related data stored locally on the current face recognition terminal device can be removed. Specifically, this can be achieved by deleting the redundant face-related data.

[0081] Although redundant face-related data is removed by the current face terminal device in this embodiment, redundant face-related data can also be removed by the first face terminal device in other embodiments of this application.

[0082] In one embodiment of this application, each face terminal device stores face-related data and identity information corresponding to the face-related data. Determining redundant face-related data includes: sending all identity information stored locally on the current face terminal device to a first face terminal device other than the current face terminal device, so that the first face terminal device can determine the first identity information stored locally from the received identity information; based on the first identity information returned by the first face terminal device, using the face-related data corresponding to the first identity information as redundant face-related data; and removing redundant face-related data from at least one face terminal device, including removing the redundant face-related data stored locally.

[0083] Both the embodiments in this application and the embodiments described above achieve cross-end alignment of face-related data. The difference between the embodiments in this application and the embodiments described above is that, in the embodiments in this application, the face terminal device for retrieving identity information is different from the face terminal device for removing redundant face-related data.

[0084] The network connection methods between current facial recognition terminal devices and the first facial recognition terminal device can be varied.

[0085] In one embodiment of this application, both the current face terminal device and the first face terminal device are face terminal devices among multiple face terminal devices, and the network connection between the face terminal devices among the multiple face terminal devices is a Bluetooth connection.

[0086] In other embodiments of this application, the current face terminal device is connected to the first face terminal device through a local area network or other means.

[0087] In one embodiment of this application, the multiple facial recognition terminal devices are facial recognition terminal devices corresponding to the same store.

[0088] Specifically, each facial recognition terminal is installed in the store and used to provide facial recognition payment services.

[0089] In this embodiment, each facial recognition terminal device is set up on a store-by-store basis, and each store can set up multiple facial recognition terminal devices. This embodiment manages the facial recognition terminal devices corresponding to the same store.

[0090] If facial recognition terminal devices in different stores can communicate with each other, it may lead to the leakage of privacy data and other information, posing a security risk. The embodiments of this application manage facial-related data of facial recognition terminal devices corresponding to each store on a store-by-store basis, which can ensure data security.

[0091] In one embodiment of this application, the face recognition terminal device stores the store identification information of the store where it is located, and the face recognition terminal device maintains a Bluetooth connection only with other face recognition terminal devices that store the same store identification information.

[0092] Specifically, once a facial recognition terminal device establishes a Bluetooth connection with another facial recognition terminal device, it will verify the store identification information. For example, one facial recognition terminal device will send store identification information to another facial recognition terminal device. If the other facial recognition terminal device determines that the two facial recognition terminal devices correspond to the same store identification information based on the received store identification information, it will maintain the Bluetooth connection; otherwise, it will disconnect the Bluetooth connection.

[0093] When different stores are too close together, facial recognition devices within different stores may mistakenly connect, potentially leading to data leakage. In this embodiment, by setting store identification information, data communication is only possible between facial recognition devices located within the same store, thus ensuring data security.

[0094] Different facial recognition terminal devices or facial recognition terminal devices in different stores can be the same or different types of facial recognition terminal devices.

[0095] In one embodiment of this application, any two face terminal devices are of the same type.

[0096] Specifically, all facial recognition terminal devices can adopt this approach. Figure 2 The facial recognition terminal device shown in this embodiment is equipped with a Bluetooth module. It can be manufactured by the same company and supplied to various stores. During production, each facial recognition terminal device can be assigned corresponding device identification information, which is then stored in the device's storage unit. Each facial recognition terminal device can communicate with the cloud via wired or wireless network. When providing facial recognition terminal devices to stores, a mapping table between the device identification information of the facial recognition terminal devices and the corresponding store identification information can be established and stored in the cloud.

[0097] Once a store deploys and activates a facial recognition terminal device, the device retrieves the corresponding device identification information from its local storage unit and then sends a query request carrying the device identification information to the cloud. The cloud can then retrieve the corresponding store identification information from the mapping table. Finally, the facial recognition terminal device receives the store identification information returned by the cloud based on the query request.

[0098] Although in this embodiment, the store identification information is obtained by the facial recognition terminal device from the cloud, in other embodiments, the store identification information can be obtained in other ways. For example, before providing facial recognition terminal devices to various stores, the corresponding store identification information or the device identification information of the store identification information can be burned into the storage unit of the facial recognition terminal device according to the stores to which the shipment is needed. In this way, when the facial recognition terminal device is started, the facial recognition terminal device can directly obtain the store identification information.

[0099] Although the removal of redundant face-related data in the above embodiments is performed by the face terminal device, the face-related data management method provided in this application embodiment can also be performed by the cloud.

[0100] Figure 5 Another embodiment according to this application is shown. Figure 3 A flowchart detailing the steps in the process.

[0101] Please see Figure 5 Specifically, this may include the following steps:

[0102] In step 310, redundant face-related data is determined based on the face-related data that has been sent to multiple face terminal devices, wherein each face terminal device stores the face-related data sent to it.

[0103] The steps in this embodiment can be executed by the cloud. In this embodiment, the face-related data stored in each face terminal device comes from the cloud; therefore, the cloud can determine which face-related data was sent to which face terminal device.

[0104] In one embodiment of this application, determining redundant face-related data based on face-related data sent to multiple face terminal devices includes: using face-related data sent to multiple face terminal devices simultaneously as redundant face-related data.

[0105] If a person's face-related data is simultaneously sent from the cloud to multiple face-related terminal devices, and each face-related terminal device stores the received face-related data, then that face-related data is redundant.

[0106] Specifically, the cloud can store a mirror image of face-related data that has been sent to various face terminal devices. Based on this mirror image data, if it is determined that a face-related data has been sent to multiple face terminal devices at the same time, then the face-related data can be determined to be redundant face-related data.

[0107] In other embodiments of this application, the cloud stores face-related data and identity information corresponding to the face-related data. After the cloud sends face-related data to a face terminal device, the cloud stores the device identification information of the face terminal device and the identity information corresponding to the face-related data. The cloud determines the face-related data that has been sent to multiple face terminal devices at the same time based on the device identification information and the corresponding stored identity information.

[0108] In step 320", a removal instruction is sent to at least one face terminal device to remove redundant face-related data from at least one face terminal device.

[0109] Specifically, a removal instruction can be sent to a randomly selected face terminal device, or it can be sent to one or more face terminal devices that store redundant face-related data, determined according to specific rules.

[0110] In one embodiment of this application, each face terminal device stores face-related data and identity information corresponding to the face-related data. Redundant face-related data is determined based on face-related data sent to multiple face terminal devices, including: receiving identity information from each face terminal device; using the face-related data corresponding to the identity information sent by multiple face terminal devices as redundant face-related data; and sending a removal instruction to at least one face terminal device to remove the redundant face-related data from the at least one face terminal device, including: sending a removal instruction to at least one face terminal device to remove the redundant face-related data and the identity information corresponding to the redundant face-related data from the at least one face terminal device.

[0111] The removal instruction can carry identity information corresponding to redundant face-related data, enabling the face terminal device that receives the removal instruction to perform the corresponding removal operation of redundant face-related data based on the identity information in the removal instruction.

[0112] In this embodiment, identity information is directly obtained from the face terminal device, and redundant face-related data is determined and removed based on the identity information. While removing redundant face-related data, the corresponding identity information is also removed. Therefore, even if some face-related data is removed from the face terminal device, the cloud can accurately determine the distribution of redundant face-related data on the face terminal device and remove it accordingly.

[0113] After identifying redundant face-related data, various methods can be used to determine the face terminal devices that need to undergo redundant face-related data removal. For example, one method could be... Figure 6 The method is shown in the embodiment. Figure 6 A flowchart illustrating the process of removing redundant face-related data according to a removal strategy based on an embodiment of this application is shown, with reference to... Figure 6 As shown, it includes the following steps:

[0114] In step 610, the culling policy corresponding to the specified time is obtained.

[0115] The elimination strategy is a method for identifying face terminal devices that store redundant face-related data and determine which face terminal devices need to have redundant face-related data eliminated. Different elimination strategies can use different methods.

[0116] Both the specified time and the corresponding removal strategy can be configured by the user. One or more specified time periods can be configured, and the same or different removal strategies can be configured for each specified time period.

[0117] In one embodiment of this application, the time intervals between multiple specified times are the same.

[0118] In this embodiment of the application, since the time intervals between multiple specified times are the same, the elimination strategy is set periodically.

[0119] In step 620, based on the current time reaching the specified time, the target face terminal device is determined according to the elimination strategy corresponding to the specified time.

[0120] Among them, the target face terminal device is the face terminal device that needs to remove redundant face-related data.

[0121] When the current time reaches the specified time, the program will be triggered to identify the target face terminal device and remove redundant face-related data from the target face terminal device.

[0122] In step 630, a removal instruction is sent to the target face terminal device to remove redundant face-related data from the target face terminal device.

[0123] By using the elimination strategy, target face terminal devices suitable for eliminating redundant face-related data can be identified. Then, by performing the elimination operation on the target face terminal devices, redundant face-related data can be eliminated more reasonably.

[0124] In this embodiment, users can configure a specified time and a corresponding elimination strategy. Then, the system can automatically identify target face terminal devices at the specified time according to the corresponding elimination strategy and perform data elimination on the target face terminal devices. This can meet different personalized data elimination needs of users. At the same time, since the elimination strategy can change dynamically, it can ensure that the identified target face terminal devices that need data elimination can be screened more scientifically, and ultimately improve the accuracy of eliminating redundant face-related data.

[0125] Figure 7 A flowchart illustrating the sending of face-related data and identity information to a face terminal device according to an embodiment of this application is shown. Figure 7 The steps in the embodiments can also be performed in the cloud. See [reference needed]. Figure 7 As shown, it includes the following steps:

[0126] In step 710, face data sent by the face terminal device is received.

[0127] The embodiments of this application can realize offline face recognition, that is, face recognition can be performed locally on the face terminal device. Offline face recognition requires face-related data to be stored locally on the face terminal device or other face terminal devices that have a network connection with the face terminal device.

[0128] Facial data refers to data that needs to be used for facial recognition. Facial data can be a facial photograph, facial feature data, or video data containing facial image frames. When the facial data is facial feature data, it can be extracted from the facial image. When the facial recognition terminal device is... Figure 2 In the embodiment shown, facial data can be collected by a camera installed on the facial terminal device; of course, in other embodiments of this application, facial data can also be collected by other devices that establish a communication connection with the facial terminal device.

[0129] In one embodiment of this application, the face terminal device has a camera, and the face data is a face photo extracted from the face streaming data collected by the camera.

[0130] Specifically, facial streaming data can include multiple facial image frames. A facial image frame can be extracted from multiple facial image frames as a facial photograph. The extracted facial image frame can be the optimal facial image frame selected by comprehensively evaluating factors such as face size, face angle, image contrast, image brightness, and sharpness.

[0131] In one embodiment of this application, the camera on the face terminal device is a 3D camera.

[0132] 3D cameras can capture spatial and depth information of a face, enabling liveness detection and ultimately improving the accuracy of facial recognition.

[0133] In step 720, based on the matching of the face data with pre-stored face-related data, the face-related data and the identity information corresponding to the face-related data are sent to the face terminal device.

[0134] When both the facial data and the pre-stored facial-related data are facial feature data, they can be directly compared using a facial recognition model to obtain a similarity score output by the model corresponding to each facial-related data. The facial-related data with the highest similarity score can be used as the facial data that matches the facial data. However, when the facial data is a facial image and the pre-stored facial-related data is facial feature data, the cloud can first extract features from the facial data to obtain the corresponding facial feature data, and then compare the pre-stored facial-related data with the facial feature data.

[0135] In one embodiment of this application, all face terminal devices are connected to each other via a network. Receiving face data sent by the face terminal devices includes: receiving face data sent by the face terminal devices when no face-related data matching the face data is found.

[0136] In one embodiment of this application, receiving face data sent by a face terminal device based on the absence of face-related data matching the face data includes: receiving face data sent by the face terminal device based on the absence of face-related data matching the face data retrieved locally from the face terminal device.

[0137] Specifically, facial recognition terminal devices often do not store all facial-related data. Even with multiple facial recognition terminal devices, some data may be missing. There is also an extreme case where no facial recognition terminal device stores any data at all. In these situations, facial recognition cannot be performed on the facial data alone. Therefore, to achieve facial recognition, the facial recognition terminal device needs to send the facial data to the cloud. To ensure that subsequent facial recognition terminals no longer rely on the cloud (and can utilize locally stored facial data for facial recognition), the cloud needs to send previously unstored facial data to the facial recognition terminal device.

[0138] The face-related data management method provided in this application embodiment can be used in face-scanning payment scenarios.

[0139] In one embodiment of this application, the method for managing face-related data further includes: matching face data with pre-stored face-related data, and performing a payment operation on the payment account corresponding to the face-related data.

[0140] Specifically, the cloud can store facial recognition data and corresponding payment accounts. Each payment account has a designated payment account. After the payment account is identified, the payment operation is performed, realizing facial recognition payment. Furthermore, the client of the facial recognition terminal device is also bound to the merchant's account. The facial recognition terminal device can send the merchant's account, facial data, and payment amount to the cloud. After the cloud identifies the payment account that matches the facial data, it transfers the payment amount from the payment account corresponding to the facial recognition account to the account corresponding to the merchant's account.

[0141] The embodiments of this application can also utilize other methods for facial recognition payment.

[0142] Figure 8 A flowchart illustrating a face recognition-based payment method according to an embodiment of this application is shown. Figure 8 The steps in the embodiments can also be performed in the cloud. See [reference needed]. Figure 8 As shown, it includes the following steps:

[0143] In step 810, the identity information sent by the face terminal device is received.

[0144] The identity identification information is sent by the facial recognition terminal device after it acquires facial data, based on the facial-related data that matches the facial data retrieved from multiple facial recognition terminal devices. The identity identification information corresponds to the retrieved facial-related data.

[0145] Multiple facial recognition terminal devices can be connected via Bluetooth or other means to establish a local area network connection.

[0146] The face-related data stored on a single face terminal device is limited. When performing face recognition, the embodiments of this application can perform cross-device retrieval.

[0147] Specifically, the facial recognition terminal device that receives the facial recognition payment request will search for facial-related data locally based on the facial data, and will also send the facial data to other facial recognition terminal devices among multiple facial recognition terminal devices, which will then search for facial-related data. The sending of facial data to other facial recognition terminal devices can be done when no matching facial-related data is found locally.

[0148] The facial recognition terminal device that has acquired facial data can sequentially send the facial data to other facial recognition terminal devices; to improve retrieval efficiency, it can also send the facial data to other facial recognition terminal devices simultaneously. When other facial recognition terminal devices retrieve facial-related data that matches the facial data, they will return the identity information corresponding to that facial-related data as the retrieval result to the facial recognition terminal device that acquired the facial data.

[0149] In one embodiment of this application, the identity information is the search result returned by other face terminal devices besides the face terminal device itself, which is first received by the face terminal device.

[0150] Specifically, redundant face-related data may exist on each face recognition terminal device, resulting in multiple search results. However, since multiple face recognition terminal devices correspond to the same store, and the number of face recognition terminal devices set up within the same store is limited, the overall amount of face-related data stored by these terminal devices is relatively small, leading to a low false recognition rate. This application's embodiment, by using the first received search result as the final result, can improve the efficiency of face recognition and facial payment while ensuring recognition accuracy.

[0151] In step 820, a payment operation is performed on the payment account corresponding to the identity information.

[0152] The identification information here can be a payment account. Making a payment is the process of transferring funds from the payment account to the merchant's account.

[0153] Although in this embodiment of the application, the face terminal device that sends the identity information is the face terminal device that obtains the face data, in other embodiments of the application, the face terminal device that sends the identity information may also be the face terminal device that stores the identity information.

[0154] Facial recognition is one of the most time-consuming steps in the facial recognition payment process. Figure 8 In the illustrated embodiment, face retrieval is performed across multiple face terminal devices, achieving cross-device face recognition without uploading face data to the cloud. Since multiple face terminal devices can be located within a local area network, face retrieval across multiple face terminal devices can greatly improve face retrieval efficiency, thereby improving the efficiency of face payment.

[0155] Therefore, the process of making payments using facial recognition can be varied and is not limited to those shown in the above embodiments.

[0156] For example, identity information can be a payment account. After acquiring facial data, the facial recognition terminal sends it to other facial recognition terminal devices. If a matching facial data is found in one of these devices, the receiving terminal will receive the payment account information and display it along with a confirmation button. This allows the user to verify the account's ownership. After clicking the confirmation button, the receiving terminal sends the payment account information to the cloud for payment processing. Similarly, if the facial recognition terminal sends the acquired facial data to the cloud, the cloud can also retrieve and return the corresponding payment account information to the receiving terminal, displaying it there. Once the user confirms the payment account belongs to them, the cloud processes the payment. This process allows for secondary verification during facial recognition payment, further enhancing its security.

[0157] Figure 9 A flowchart illustrating the process of removing redundant face-related data according to an embodiment of this application is shown. Please refer to... Figure 9 This includes the following steps:

[0158] In step 910, the second face terminal device is determined based on the frequency with which the payment account corresponding to the redundant face-related data makes payments through each face terminal device. Among the multiple face terminal devices, the payment account corresponding to the redundant face-related data makes payments through the third face terminal device more frequently than the second face terminal device.

[0159] Specifically, if user L appears on both device A and device B in the same store, but user L is clearly used more frequently on device A than on device B, then user L's facial data on device B can be removed first.

[0160] In step 920, a removal instruction is sent to the second face terminal device to remove redundant face-related data from the second face terminal device.

[0161] The steps in this application embodiment can be a rejection strategy used in the foregoing embodiments.

[0162] In this embodiment, it is possible to ensure that users can quickly and directly identify the results on devices that are used frequently, without having to query across devices again, which greatly improves the efficiency of face recognition and thus enhances the user experience.

[0163] Figure 10 A block diagram illustrating the overall architecture of the technical solutions that can implement the embodiments of this application is shown. Below, in conjunction with... Figure 10 The embodiments of this application are further described below.

[0164] The overall architecture includes a backend service, facial recognition payment device A, and facial recognition payment device B. The backend service can be located in the cloud, specifically deployed on a cloud server or server cluster. The backend service comprises multiple sub-modules, each of which can be implemented using one or more servers within the server cluster.

[0165] The backend service includes a master face database, which stores facial feature data. It also includes mirror images of the face-related data stored on each face payment device. For example, face database A is a mirror image of the data stored on face payment device A, and face database B is a mirror image of the data stored on face payment device B. Based on these mirror images, redundant face-related data can be identified and stored on each face payment device.

[0166] Please see Figure 10 The backend services also include policy services and timing services. The policy service provides policies for managing face-related data, and the timing service provides the execution time of the policies. The policy service and the timing service work together to periodically optimize the storage of face-related data stored on face payment devices and remove redundant face-related data.

[0167] Please continue reading Figure 10 The backend services also include basic account services, cloud-based facial payment services, and database update services. In the WeChat Pay scenario, the basic account service is related to the WeChat account system's relationship chain. Upon successful facial recognition, this service is invoked to obtain the current user's identity information. The cloud-based facial payment service functions as follows: after receiving facial data uploaded from the facial payment device, it extracts features from the facial data and compares the extracted facial features with those in the overall facial feature database to find the highest-scoring facial feature. Within the WeChat system, it can ultimately return the user's WeChat account or WeChat Pay payment code information to the facial payment device. The database update service is a long-lived connection between the facial payment device and the backend services, used to periodically receive CRUD (Create, Read, Update, Delete) operations from the backend services on the device's facial database.

[0168] The architecture of each facial recognition payment device is the same. Both facial recognition payment device A and facial recognition payment device B include a 3D camera, an Android OS (operating system), and a facial recognition APP. The facial recognition APP includes a facial recognition module, a Bluetooth module, a database update module, and a facial database. The database update module in the facial recognition payment device is mainly used to receive facial-related data and user account information within the WeChat system sent by the backend service. The facial recognition module specifically includes a facial acquisition submodule and a facial selection submodule. The working process of a facial recognition payment device is as follows: First, a 3D camera captures facial streaming data, including multiple facial image frames. Then, the facial streaming data is sent via Android OS to the facial recognition module in the facial recognition app for facial capture and selection, resulting in facial data. Next, the facial data is searched in a facial database. If no matching facial data is found, the facial data is sent via Bluetooth to other facial recognition payment devices for further searching. If no matching facial data is found on any of the facial recognition payment devices, the facial recognition payment device sends the facial data to a backend service for further facial recognition.

[0169] In summary, the face-related data management method provided in this application first identifies redundant face-related data stored simultaneously on multiple face terminal devices, and then removes this redundant face-related data from at least one face terminal device that stores it. This reduces the overall storage resources consumed by each face terminal device in storing face-related data, alleviates the problem of rapidly increasing storage space occupied on face terminal devices to a certain extent, improves storage efficiency, and significantly reduces storage costs. Simultaneously, continuing to store the redundant face-related data on at least one face terminal device ensures its availability. Therefore, the technical solution provided in this application can both reduce the consumption of storage resources for storing face-related data and ensure the availability of face-related data, achieving scientific and efficient management of face-related data. Furthermore, for each redundant face-related data, this application embodiment can also prioritize removing redundant face-related data from face terminal devices that use it less frequently, improving face recognition efficiency and user experience.

[0170] The following describes an embodiment of the apparatus described in this application, which can be used to execute the face-related data management method described in the above embodiments of this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the face-related data management method described in the above applications.

[0171] Figure 11A block diagram of a face-related data management apparatus according to an embodiment of this application is shown.

[0172] Reference Figure 11 As shown, a face-related data management device 1100 according to an embodiment of this application includes: a determination unit 1110 and a rejection unit 1120.

[0173] The determining unit 1110 is used to determine redundant face-related data, which is face-related data stored on at least two face terminal devices and is data used to identify face information; the eliminating unit 1120 is used to eliminate the redundant face-related data from at least one face terminal device and continue to store the redundant face-related data on at least one face terminal device other than the at least one face terminal device.

[0174] In some embodiments of this application, based on the aforementioned scheme, each face terminal device stores face-related data and identity information corresponding to the face-related data. The determining unit 1110 is configured to: if, based on the first identity information sent by a first face terminal device other than the current face terminal device, it is determined that the first identity information is stored locally on the current face terminal device, then the face-related data corresponding to the first identity information is regarded as redundant face-related data; the elimination unit 1120 is configured to: eliminate the redundant face-related data stored locally.

[0175] In some embodiments of this application, based on the aforementioned scheme, the determining unit 1110 is configured to: determine redundant face-related data based on face-related data sent to multiple face terminal devices, wherein each face terminal device stores face-related data sent to it; the eliminating unit 1120 is configured to: send an eliminating instruction to the at least one face terminal device to eliminate the redundant face-related data from the at least one face terminal device.

[0176] In some embodiments of this application, based on the aforementioned scheme, the elimination unit 1120 is configured to: obtain the elimination strategy corresponding to the specified time; determine the target face terminal device according to the elimination strategy corresponding to the specified time based on the current time reaching the specified time, wherein the target face terminal device is a face terminal device that needs to have redundant face-related data eliminated; and send an elimination instruction to the target face terminal device to eliminate the redundant face-related data from the target face terminal device.

[0177] In some embodiments of this application, based on the aforementioned scheme, the determining unit 1110 is further configured to: receive face data sent by the face terminal device; and send the face-related data and the identity identification information corresponding to the face-related data to the face terminal device according to the face data matching with pre-stored face-related data.

[0178] In some embodiments of this application, based on the aforementioned scheme, each of the multiple face terminal devices is connected to a network, and the determining unit 1110 is configured to receive face data sent by the face terminal device when no face-related data matching the face data is found.

[0179] In some embodiments of this application, based on the foregoing scheme, the determining unit 1110 is further configured to: perform a payment operation on the payment account corresponding to the face-related data by matching the face data with pre-stored face-related data.

[0180] In some embodiments of this application, based on the foregoing scheme, the determining unit 1110 is further configured to: receive identity identification information sent by a face terminal device, wherein the identity identification information is sent by the face terminal device after acquiring face data based on face-related data retrieved from the plurality of face terminal devices that matches the face data, and the identity identification information corresponds to the retrieved face-related data; and perform a payment operation on the payment account corresponding to the identity identification information.

[0181] In some embodiments of this application, based on the aforementioned scheme, the elimination unit 1120 is configured to: determine a second face terminal device based on the frequency of payment made by the payment account corresponding to the redundant face-related data through each face terminal device, wherein the payment account corresponding to the redundant face-related data among the plurality of face terminal devices makes payments through a third face terminal device more frequently than the second face terminal device; and send an elimination instruction to the second face terminal device to eliminate the redundant face-related data from the second face terminal device.

[0182] In some embodiments of this application, based on the foregoing scheme, the identity information is the search result returned by other face terminal devices besides the face terminal device itself, which is first received by the face terminal device.

[0183] In some embodiments of this application, based on the aforementioned scheme, the network connection between the multiple face terminal devices is a Bluetooth connection.

[0184] In some embodiments of this application, based on the foregoing scheme, the face terminal device has a camera, and the face data is a face photo extracted from face streaming media data collected by the camera.

[0185] Figure 12 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown.

[0186] It should be noted that, Figure 12 The computer system 1200 of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0187] like Figure 12 As shown, the computer system 1200 includes a Central Processing Unit (CPU) 1201, which can perform various appropriate actions and processes based on programs stored in Read-Only Memory (ROM) 1202 or programs loaded from storage portion 1208 into Random Access Memory (RAM) 1203, such as performing the methods described in the above embodiments. Various programs and data required for system operation are also stored in RAM 1203. The CPU 1201, ROM 1202, and RAM 1203 are interconnected via bus 1204. An Input / Output (I / O) interface 1205 is also connected to bus 1204.

[0188] The following components are connected to I / O interface 1205: an input section 1206 including a keyboard, mouse, etc.; an output section 1207 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 1208 including a hard disk, etc.; and a communication section 1209 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 1209 performs communication processing via a network such as the Internet. A drive 1210 is also connected to I / O interface 1205 as needed. Removable media 1211, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 1210 as needed so that computer programs read from them can be installed into storage section 1208 as needed.

[0189] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1209, and / or installed from removable medium 1211. When the computer program is executed by central processing unit (CPU) 1201, it performs various functions defined in the system of this application.

[0190] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such transmitted data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0191] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0192] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0193] In one aspect, this application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform the methods described in the above embodiments.

[0194] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0195] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the method according to the embodiments of this application.

[0196] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0197] The data collection and processing plan outlined in this application must be implemented in strict accordance with the requirements of relevant national laws and regulations, obtaining the informed consent or separate consent of the data subject (or having a legal basis as stipulated by the relevant national laws and regulations), and conducting subsequent data use and processing within the scope authorized by laws and regulations and the data subject.

[0198] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for managing face-related data, characterized in that, The method includes: Redundant face-related data is identified, wherein the redundant face-related data is face-related data stored on at least two face terminal devices, and the face-related data is data used to identify face information. Each face terminal device stores face-related data and identity identification information corresponding to the face-related data. The identification of redundant face-related data includes: if, based on the first identity identification information sent by a first face terminal device other than the current face terminal device, it is determined that the first identity identification information is stored locally on the current face terminal device, then the face-related data corresponding to the first identity identification information is taken as redundant face-related data. The redundant face-related data is removed from at least one face terminal device, and the redundant face-related data is stored on at least one face terminal device other than the at least one face terminal device; the removal of the redundant face-related data from at least one face terminal device includes: removing the redundant face-related data stored locally.

2. The method for managing face-related data according to claim 1, characterized in that, The determination of redundant face-related data includes: Based on the face-related data that has been sent to multiple face terminal devices, redundant face-related data is identified, wherein each face terminal device stores the face-related data sent to it. The step of removing the redundant face-related data from at least one face terminal device includes: Send a removal instruction to the at least one face terminal device to remove the redundant face-related data from the at least one face terminal device.

3. The method for managing face-related data according to claim 2, characterized in that, Sending a removal instruction to the at least one face terminal device to remove redundant face-related data from the at least one face terminal device includes: Get the removal policy corresponding to the specified time period in the configuration; Based on the current time reaching the specified time, and according to the elimination strategy corresponding to the specified time, the target face terminal device is determined, wherein the target face terminal device is the face terminal device that needs to have redundant face-related data eliminated. A removal instruction is sent to the target face terminal device to remove the redundant face-related data from the target face terminal device.

4. The method for managing face-related data according to claim 2, characterized in that, The method further includes: Receive facial data sent by facial recognition terminal devices; Based on the matching of the facial data with pre-stored facial-related data, the facial-related data and the identity information corresponding to the facial-related data are sent to the facial terminal device.

5. The method for managing face-related data according to claim 4, characterized in that, Each of the plurality of facial recognition terminal devices is connected to a network, and receiving facial data sent by the facial recognition terminal devices includes: Receive the face data sent by the face terminal device when no face-related data matching the face data is found.

6. The method for managing face-related data according to claim 5, characterized in that, The method further includes: The system matches the facial data with pre-stored facial-related data and performs payment operations on the payment account corresponding to the facial-related data.

7. The method for managing face-related data according to claim 5, characterized in that, The method further includes: The system receives identity identification information from a face recognition terminal device. This identity identification information is sent by the face recognition terminal device after acquiring face data, based on face-related data retrieved from multiple face recognition terminal devices that matches the face data. The identity identification information corresponds to the retrieved face-related data. Perform payment operations on the payment account corresponding to the identity information.

8. The method for managing face-related data according to claim 7, characterized in that, Sending a removal instruction to the at least one face terminal device to remove redundant face-related data from the at least one face terminal device includes: The second face terminal device is determined based on the frequency with which the payment account corresponding to the redundant face-related data makes payments through each face terminal device. Among the multiple face terminal devices, the frequency with which the payment account corresponding to the redundant face-related data makes payments through the third face terminal device is higher than that of the second face terminal device. A removal instruction is sent to the second face terminal device to remove the redundant face-related data from the second face terminal device.

9. The method for managing face-related data according to claim 7, characterized in that, The identity information is the search result returned by other face terminal devices besides the face terminal device itself, which is first received by the face terminal device.

10. The method for managing face-related data according to claim 6, characterized in that, The network connection between the various face terminal devices is a Bluetooth connection.

11. The method for managing face-related data according to claim 5, characterized in that, The facial recognition terminal device has a camera, and the facial data is a facial photograph extracted from the facial streaming data collected by the camera.

12. A device for managing face-related data, characterized in that, The device includes: A determining unit is configured to determine redundant face-related data, wherein the redundant face-related data is face-related data stored on at least two face terminal devices, and the face-related data is data used to identify face information. Each face terminal device stores face-related data and identity identification information corresponding to the face-related data. The determining unit is configured to: if, based on the first identity identification information sent by a first face terminal device other than the current face terminal device, it is determined that the first identity identification information is stored locally on the current face terminal device, then the face-related data corresponding to the first identity identification information is taken as redundant face-related data. A removal unit is configured to remove the redundant face-related data from at least one face terminal device and continue to store the redundant face-related data on at least one face terminal device other than the at least one face terminal device; the removal unit is configured to remove the redundant face-related data stored locally.

13. A computer-readable medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for managing face-related data as described in any one of claims 1 to 11.

14. An electronic device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the method for managing face-related data as described in any one of claims 1 to 11.

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