WO2023173666A1 - 人脸支付方法、装置、电子设备、存储介质、程序和产品 - Google Patents

人脸支付方法、装置、电子设备、存储介质、程序和产品 Download PDF

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WO2023173666A1
WO2023173666A1 PCT/CN2022/111405 CN2022111405W WO2023173666A1 WO 2023173666 A1 WO2023173666 A1 WO 2023173666A1 CN 2022111405 W CN2022111405 W CN 2022111405W WO 2023173666 A1 WO2023173666 A1 WO 2023173666A1
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payment
target
terminal group
face
preset
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PCT/CN2022/111405
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English (en)
French (fr)
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程前
徐建兴
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上海商汤智能科技有限公司
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Publication of WO2023173666A1 publication Critical patent/WO2023173666A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/38—Payment protocols; Details thereof
    • G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
    • G06Q20/401—Transaction verification
    • G06Q20/4014—Identity check for transactions
    • G06Q20/40145—Biometric identity checks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/22—Matching criteria, e.g. proximity measures

Definitions

  • the present disclosure relates to the field of Internet technology, and relates to but is not limited to a facial payment method, device, electronic device, storage medium, computer program and computer program product.
  • the face image to be verified will be compared with the full face image library of the payment system; however, as the number of users of the face payment system continues to increase, the pre-stored registered user faces
  • the order of magnitude of face base maps is getting larger and larger, which brings about problems such as low efficiency and success rate of face recognition verification, and slow response speed of face payment.
  • Embodiments of the present disclosure provide a face payment method, device, electronic device, storage medium, program and product, which can improve the face recognition verification efficiency and success rate, thereby effectively improving the face payment response speed.
  • the technical solutions of the embodiments of the present disclosure are as follows:
  • a face payment method including:
  • identity verification is performed on the face image to be verified to obtain a first identity verification result.
  • the target face image set provides payment for the target terminal group.
  • the target face image set includes a target face registration image that matches the to-be-verified face image
  • the above technical solution determines that the face payment request corresponds to the target terminal group to which the target payment terminal belongs, and divides the registered face image set for the payment terminal to provide payment services according to the terminal group, which can effectively Reduce the amount of data required for face verification and recognition, improve the efficiency and success rate of face verification and recognition, and thus effectively improve the response speed of face payment.
  • the method further includes:
  • a face image set corresponding to the same terminal group is constructed.
  • the above technical solution combines the associated business information corresponding to the payment terminal to divide the terminal groups. It can be based on the same associated business information and is often oriented to the attributes of the same user group, greatly improving the user overlap of payment terminals in the terminal group. This can increase the probability that payment terminals in the terminal group share the same face image set, effectively improving the efficiency and success rate of face image recognition verification.
  • the method further includes:
  • a face image set corresponding to the same terminal group is constructed.
  • the above technical solution combined with the location information corresponding to the payment terminal, is used to divide terminal groups. It can be based on the attributes of the same area and often for the same user group, greatly improving the user overlap of payment terminals in the terminal group, and thus improving the The probability that payment terminals in a terminal group share the same face image set effectively improves the efficiency and success rate of face image recognition verification.
  • the method further includes:
  • the payment analysis result represents the payment of the multiple preset objects to multiple preset payment terminals in the current cycle. Probability of use;
  • a face image set of the terminal group corresponding to the object group is constructed.
  • the above technical solution performs payment analysis on a preset object based on the payment operation information obtained on a periodic basis, which can effectively improve the accuracy of the determined payment analysis results on the object's payment terminal usage, and thus can better improve the determined payment terminal usage.
  • the user coincidence degree of the payment terminal in the terminal group and the probability that the payment terminals in the terminal group share the same face image set can effectively improve the efficiency and success rate of face image recognition verification during face payment processing.
  • grouping the plurality of preset objects based on the initial terminal group to obtain the object group includes:
  • the above technical solution divides the preset objects corresponding to the same initial terminal group into an object group, which can effectively increase the probability that the payment terminals in the corresponding terminal group share the same face image set, thereby effectively improving the human face image set. Face image recognition verification efficiency and success rate.
  • grouping the plurality of preset objects based on the initial terminal group to obtain the object group includes:
  • the above technical solution divides a preset number of the same payment terminals in the corresponding initial terminal group into an object group, which can effectively improve the probability that the payment terminals in the corresponding terminal group share the same face image set. probability, thereby effectively improving the efficiency and success rate of face image recognition verification.
  • performing payment analysis on the plurality of preset objects based on the payment operation information, and obtaining payment analysis results includes:
  • the payment operation information is input into a preset payment analysis network for payment analysis, and the payment analysis result is obtained.
  • the above technical solution combined with the preset payment analysis network for payment analysis, can improve the accuracy of predicting the probability of using multiple preset payment terminals by multiple preset objects, thereby improving the effectiveness of payment analysis.
  • the method further includes:
  • the first identity verification result indicates that the target face image set does not include a target face registration image that matches the face image to be verified, based on the full face image set, the person to be verified is Face image is used for identity verification, and the second identity verification result is obtained;
  • the second identity verification result indicates that the full face image set includes the target face registration image
  • a payment operation is performed based on the payment account corresponding to the target face registration image.
  • the first identity verification result indicates that the target face image set does not include a target face registration image that matches the face image to be verified
  • identity verification is performed on the face image to be verified in combination with the full face image set. , which can effectively improve the success rate of face payment verification during face payment processing.
  • determining the target terminal group to which the target payment terminal belongs includes:
  • the target terminal group identification including the target terminal identification from a plurality of preset terminal group identifications
  • the terminal group corresponding to the target terminal group identifier is used as the target terminal group.
  • the above technical solution queries the target terminal group ID including the target terminal ID from multiple preset terminal group IDs, which can facilitate subsequent face verification by group, thereby effectively improving the user experience in the face payment processing process. Face image recognition verification efficiency and success rate.
  • a face payment device including:
  • the receiving part is configured to receive a face payment request sent by the target payment terminal, where the face payment request includes a face image to be verified;
  • the first determining part is configured to determine the target terminal group corresponding to the target payment terminal
  • the first verification part is configured to perform identity verification on the face image to be verified based on the target face image set corresponding to the target terminal group, and obtain the first identity verification result.
  • the target face image set A registered face image set of a target object group that provides payment services to the target terminal group;
  • a first operation execution part configured to perform, in the case where the first identity verification result indicates that the target face image set includes a target face registration image that matches the face image to be verified, based on the target
  • the payment account corresponding to the face registration image performs the payment operation.
  • the device further includes:
  • the first acquisition part is configured to acquire associated business information corresponding to multiple preset payment terminals
  • the first dividing part is configured to divide the preset payment terminals corresponding to the same associated business information into the same terminal group;
  • the first construction part is configured to construct a face image set corresponding to the same terminal group based on the registered face images corresponding to the same terminal group.
  • the device further includes:
  • the second acquisition part is configured to obtain location information corresponding to multiple preset payment terminals
  • the second dividing part is configured to perform, based on the location information, dividing the preset payment terminals in the preset area into the same terminal group;
  • the second construction part is configured to construct a face image set corresponding to the same terminal group based on the registered face images corresponding to the same terminal group.
  • the device further includes:
  • the third acquisition part is configured to obtain the payment operation information of multiple preset objects in the previous cycle of the current cycle, where the payment operation information represents the payment operation information of the multiple preset objects to multiple preset objects in the current cycle.
  • Preset payment terminal usage information
  • the analysis part is configured to perform payment analysis on the plurality of preset objects based on the payment operation information to obtain a payment analysis result; the payment analysis result represents the payment of the plurality of preset objects in the current cycle. Probability of usage of multiple preset payment terminals;
  • the second determination part is configured to determine the initial terminal group corresponding to each of the preset objects according to the payment analysis results
  • a grouping part configured to perform grouping of the plurality of preset objects based on the initial terminal group to obtain an object group
  • the third construction part is configured to construct a face image set of the terminal group corresponding to the object group based on the registered face image corresponding to the object group.
  • the grouping part is specifically configured to divide preset objects corresponding to the same initial terminal group into the same object group.
  • the grouping part is specifically configured to divide at least two target objects among the plurality of preset objects into the same object group, and the at least two target objects are initial
  • the terminal group includes a preset number of preset objects of the same payment terminal.
  • the analysis part is specifically configured to input the payment operation information into a preset payment analysis network to perform payment analysis and obtain the payment analysis result.
  • the device further includes:
  • the second verification part is configured to perform, in the case where the first identity verification result indicates that the target face image set does not include a target face registration image that matches the face image to be verified, based on the full amount of faces. Image set, perform identity verification on the face image to be verified, and obtain the second identity verification result;
  • the second operation execution part is configured to execute the payment account number corresponding to the target face registration image based on the second identity verification result indicating that the full face image set includes the target face registration image. Perform payment operations.
  • the first determining part includes:
  • An acquisition unit configured to obtain the target terminal identification of the target payment terminal
  • a query unit configured to query a target terminal group identification including the target terminal identification from a plurality of preset terminal group identifications
  • the determining unit is configured to identify a terminal group corresponding to the target terminal group as the target terminal group.
  • an electronic device including: a processor; a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement A method as described in any one of the above.
  • a computer-readable storage medium which when instructions in the storage medium are executed by a processor of an electronic device, enables the electronic device to perform any of the above-mentioned embodiments of the present disclosure. 1. The method described.
  • a computer program including computer readable code.
  • the computer readable code When the computer readable code is executed in an electronic device, a processor in the electronic device executes for implementing any of the above. 1. The method described.
  • a computer program product containing instructions is provided.
  • the computer program product is used to store computer-readable instructions, which when executed, cause a computer to perform any of the above methods.
  • Figure 1 is a schematic diagram of an application environment of a facial payment method according to an exemplary embodiment
  • Figure 2 is a flow chart of a facial payment method according to an exemplary embodiment
  • Figure 3 is a flow chart illustrating a method of grouping payment terminals and constructing a face image set corresponding to the same terminal group according to an exemplary embodiment
  • Figure 4 is another flowchart of grouping payment terminals and constructing a face image set corresponding to the same terminal group according to an exemplary embodiment
  • Figure 5 is a flow chart illustrating a method of grouping payment terminals and constructing a face image set corresponding to the same terminal group according to an exemplary embodiment
  • Figure 6 is a flow chart illustrating a method of grouping payment terminals and constructing a face image set corresponding to the same terminal group according to an exemplary embodiment
  • Figure 7 is a block diagram of a facial payment device according to an exemplary embodiment
  • Figure 8 is a block diagram of an electronic device for face payment according to an exemplary embodiment.
  • FIG. 1 is a schematic diagram of an application environment of a facial payment method according to an exemplary embodiment.
  • the application environment may include a payment terminal 100 and a server 200.
  • the payment terminal 100 may be a terminal used to accept face payment for any user.
  • the payment terminal 100 may be a physical electronic device, or may be software running on the physical electronic device, such as an application program.
  • the payment terminal 100 may be provided with a preset camera.
  • the preset camera may be a camera integrated with the payment terminal, or may be a split camera connected in a wired or wireless manner.
  • the server 200 can provide background services for the payment terminal 100 and perform face payment processing in combination with the face images collected by the payment terminal.
  • the server 200 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers.
  • Figure 1 is only an application environment provided by an embodiment of the present disclosure. In actual applications, other application environments may also be included, for example, a mobile terminal used for face registration in advance may be included. wait.
  • the above-mentioned payment terminal 100 and server 200 can be connected directly or indirectly through wired or wireless communication methods, and the embodiment of the present disclosure is not limited here.
  • FIG. 2 is a flow chart of a face payment method according to an exemplary embodiment.
  • the face payment method can be applied to a server. As shown in Figure 2, the method can include the following steps:
  • S201 Receive the face payment request sent by the target payment terminal.
  • the target payment terminal can be any terminal that accepts face payments from users.
  • the above face payment request may include a face image to be verified; optionally, when the target payment terminal collects a face image to be verified, it may send a face payment request including the face image to be verified to the server, so that The server performs facial payment processing.
  • S203 Determine the target terminal group to which the target payment terminal belongs.
  • payment terminals in the payment system can be grouped in advance, and payment terminals in the same group are associated with the same face image set, so as to improve face verification efficiency in subsequent face payment processing.
  • payment terminals with common or similar information will often accept face payment services of users in the same user group.
  • the above method may also include the steps of grouping multiple preset payment terminals in advance and constructing a face image set corresponding to the same terminal group.
  • grouping multiple preset payment terminals Grouping payment terminals and building a face image set corresponding to the same terminal group may include:
  • the plurality of preset payment terminals may be payment terminals in the payment system.
  • the associated business information can be information that can characterize the business party to which the payment terminal belongs. For example, when the business party is a supermarket, the associated business information can be supermarket identification information, etc.
  • the preset payment corresponding to the same supermarket identification information can be Terminals are divided into the same terminal group. For example, when the business party represents a certain chain brand, the associated business information can be the chain brand logo.
  • the preset payment terminals corresponding to the same chain brand logo can be divided into the same terminal group.
  • the registered face image corresponding to any terminal group may include the registered face image of the user who performs face payment registration at the payment terminal in the terminal group and the payment terminal in the terminal group. Registered face images of users who have used face payment.
  • the terminal groups are divided based on the associated business information corresponding to the payment terminals.
  • the same associated business information can be based on the attributes of the same user group, which greatly improves the user overlap of the payment terminals in the terminal group. , which can then increase the probability that payment terminals in the terminal group share the same face image set, effectively improving the efficiency and success rate of face image recognition verification.
  • grouping multiple preset payment terminals and constructing a face image set corresponding to the same terminal group may include:
  • S403 Based on the location information, divide the preset payment terminals in the preset area into the same terminal group;
  • the location information corresponding to the multiple preset payment terminals may be information about the respective locations of the multiple preset payment terminals.
  • the preset area can be set in conjunction with actual applications, such as a preset neighborhood, a preset business district, etc., or within a preset range with the preset location as the center of the circle.
  • the location information corresponding to the payment terminal is combined to divide the terminal group, which can be based on the attributes of the same area and often for the same user group, greatly improving the user overlap of the payment terminals in the terminal group, and thus can Improve the probability that payment terminals in a terminal group share the same face image set, effectively improving the efficiency and success rate of face image recognition verification.
  • grouping multiple preset payment terminals and constructing a face image set corresponding to the same terminal group may include:
  • the plurality of preset objects may be user accounts that have registered for face payment in the payment system.
  • the above payment operation information may represent the usage information of multiple preset objects on multiple preset payment terminals in the current cycle.
  • the period for obtaining payment operation information can be set according to actual application requirements, such as one week, two weeks, etc.
  • S503 Perform payment analysis on multiple preset objects based on payment operation information, and obtain payment analysis results;
  • the above payment analysis results can represent the usage probabilities of multiple preset objects in the current period for multiple preset payment terminals.
  • the above-mentioned payment analysis is performed on multiple preset objects based on payment operation information, and obtaining the payment analysis results may include:
  • the preset payment analysis network may be obtained by performing payment analysis training on a preset deep learning network based on the payment operation information of the sample object in the first historical period and the labeled payment analysis results corresponding to the sample object.
  • the labeled payment analysis result may be the probability of the sample object using multiple sample payment terminals in the second historical period.
  • the sample object may be a user account that has registered face payment in the payment system; the first historical period may be the previous period of the second historical period; the multiple preset payment terminals may include the multiple sample payment terminals mentioned above.
  • the labeled payment analysis result corresponding to the sample object can be 1 or 0.
  • the labeled payment analysis result corresponding to the object can be 1; conversely, if the number of times a certain object in the sample object uses a certain sample payment terminal in the second historical period is less than the preset threshold, the labeled payment analysis result corresponding to the object can be The payment analysis result can be 0.
  • payment analysis is performed in combination with the preset payment analysis network, which can improve the accuracy of predicting the usage probabilities of multiple preset payment terminals by multiple preset objects, thereby improving the effectiveness of payment analysis.
  • determining the initial terminal group corresponding to each preset object based on the payment analysis results may include: determining the preset terminal group corresponding to the payment analysis result that satisfies the preset condition among the payment analysis results corresponding to each preset object. Set up a payment terminal; and build an initial terminal group of the preset object based on the preset payment terminal corresponding to the payment analysis result that meets the preset conditions.
  • the preset condition can be a preset condition for filtering out the initial terminal group.
  • the payment analysis result that satisfies the preset condition can be greater than or equal to Payout analysis results with preset probabilities.
  • preset objects corresponding to the same initial terminal group can be divided into an object group.
  • the terminal group corresponding to the object group can be the initial terminal group corresponding to the object in the object group.
  • Union of terminal groups for example, since the initial terminal groups corresponding to the objects in the object group are the same, correspondingly, the terminal group corresponding to the object group can be the initial terminal group corresponding to any object in the object group);
  • the above-mentioned grouping of multiple preset objects based on the initial terminal group, the obtained object group may include:
  • the preset objects corresponding to the same initial terminal group are divided into one object group, which can effectively increase the probability that payment terminals in the corresponding terminal group share the same face image set, thereby effectively improving Face image recognition verification efficiency and success rate.
  • a preset number of the same payment terminals in the corresponding initial terminal group can be divided into an object group, and accordingly, subsequent terminal groups corresponding to this object group , which can be the union of the initial terminal groups corresponding to the preset objects in this object group.
  • the obtained object groups may include:
  • the at least two target objects may be the default objects of a preset number of the same payment terminals included in the corresponding initial terminal group among the plurality of default objects.
  • a preset number of the same payment terminals in the corresponding initial terminal group are divided into an object group, which can effectively improve the payment terminals in the corresponding terminal group sharing the same face image set. probability, thereby effectively improving the efficiency and success rate of face image recognition verification.
  • the registered face image corresponding to the object group can be the registered face image of the object in the object group; correspondingly, the registered face image of the object in an object group can be used as the object group.
  • payment analysis of a preset object is performed on the payment operation information obtained on a periodic basis, which can effectively improve the accuracy of the determined payment analysis results in representing the payment terminal usage of the object, and thus can better improve the determined accuracy of the payment terminal usage of the object.
  • the user overlap of the payment terminals in the terminal group and the probability that the payment terminals in the terminal group share the same face image set can effectively improve the efficiency and success rate of face image recognition verification during face payment processing.
  • grouping multiple preset payment terminals and constructing a face image set corresponding to the same terminal group may include:
  • S603 Determine the number of times each preset object has used each preset payment terminal in the previous cycle based on the payment operation information of each preset object in the previous cycle;
  • S605 Based on the number of uses, determine the associated terminal group of each preset object
  • S607 Group multiple preset objects based on the associated terminal group to obtain the object group;
  • S609 Based on the registered face images corresponding to the object group, construct a face image set of the terminal group corresponding to the object group.
  • the above-mentioned determination of the associated terminal group of each preset object based on the number of uses may include, for each preset object, comparing the number of times the preset object has been used on multiple preset payment terminals with the preset number of times. In comparison, if the number of times of use corresponding to a certain preset payment terminal is greater than or equal to the preset number of times, a terminal group associated with the preset object can be constructed based on the preset payment terminals whose number of times of use is greater than or equal to the preset number.
  • the preset objects corresponding to the same associated terminal group can be divided into one object group.
  • the above-mentioned grouping of multiple preset objects based on the associated terminal group obtains the object The group may include: dividing the preset objects corresponding to the same associated terminal group into the same object group.
  • a preset number of the same payment terminals in the corresponding associated terminal group can be divided into an object group, and accordingly, subsequent terminal groups corresponding to this object group , which can be the union of the associated terminal groups corresponding to the preset objects in this object group.
  • the above-mentioned grouping of multiple preset objects based on the terminal group to obtain the object group may include: dividing at least two target objects among the multiple preset objects into the same object group, and at least two target objects
  • the associated terminal group may include a preset number of preset objects of the same payment terminal.
  • obtaining the payment operation information on a periodic basis can effectively improve the timeliness and effectiveness of the payment operation information, thereby better improving the user overlap of the payment terminals in the determined terminal group and the user overlap in the terminal group.
  • payment terminals share the same set of face images, in order to effectively improve the efficiency and success rate of face image recognition verification during face payment processing.
  • a preset terminal group identifier corresponding to each terminal group may be created.
  • the preset terminal group identifier may include Terminal identification for each payment terminal.
  • the above-mentioned preset terminal group identification information can be stored in a preset database for subsequent query.
  • the above-mentioned determination of the target terminal group to which the target payment terminal belongs includes: obtaining the target terminal identification of the target payment terminal; and querying the target terminal including the target terminal identification from multiple preset terminal group identifications. Group ID; use the terminal group corresponding to the target terminal group ID as the target terminal group.
  • querying the target terminal group identification including the target terminal identification from multiple preset terminal group identifications can facilitate subsequent face verification by group, effectively reducing the need for searching during the face verification process.
  • the number of images in the face image database is reduced, that is, the amount of data processing in the face verification process is reduced, which can effectively improve the face image recognition verification efficiency and success rate in the face payment processing process.
  • the above-mentioned target face image set may be a registered face image set of a target object group that provides payment services to the target terminal group (i.e., accepts face payment services);
  • the face image features of each face image in the target face image set and the face image features to be verified of the face image to be verified can be obtained; then, each person in the target face image set can be determined The similarity between the facial image features of the face image and the face image features to be verified; optionally, if the maximum similarity is greater than or equal to the preset similarity threshold, it can be obtained to indicate that the target face image set includes the face image to be verified The first identity verification result of the matched target face registration image; conversely, if the maximum similarity is less than the preset similarity threshold, the first identity verification result indicating that the target face image set does not include the target face registration image can be obtained.
  • the similarity between facial image features may include but is not limited to Euclidean distance, Manhattan distance, etc. between facial image features.
  • the above face payment request may also include payment information.
  • the payment information may be the amount of virtual resources that need to be consumed.
  • the first identity verification result indicates that the target face image set includes the information to be verified. In the case where the face image matches the target face registration image, the corresponding amount of virtual resources can be deducted from the payment account corresponding to the target face registration image to implement the payment operation.
  • the face payment request is determined to correspond to the target terminal group to which the target payment terminal belongs, and the payment terminals are divided according to the terminal group to provide
  • the registered face image set of the payment service can effectively reduce the amount of data required for face verification and recognition.
  • the efficiency and success rate of face verification and recognition can be improved, thereby improving the efficiency and success rate of face verification and recognition. It can also effectively improve the response speed of face payment.
  • the above method may also include:
  • identity verification is performed on the face image to be verified based on the full face image set to obtain the second Authentication results.
  • the payment operation is performed based on the payment account corresponding to the target face registration image.
  • the full face image set may be all registered face images in the payment system. For example, based on the full face image set, perform identity verification on the face image to be verified, and obtain the second identity verification result. Refer to the target face image set corresponding to the target terminal group mentioned above. Perform identity verification on the face image to be verified, and obtain Specific refinement of the first identity verification result.
  • the identity of the face image to be verified is combined with the full face image set. Verification can effectively improve the success rate of face payment verification during face payment processing.
  • Embodiments of the present disclosure can be applied to face-intensive payment scenarios such as retail stores and supermarkets, and can also be applied to smart convenience stores, unmanned vending machines, unmanned convenience stores, and other scenarios that require face payment; and related Compared with the solution in the technology that requires face verification in the entire face image set including massive face images, the embodiment of the present disclosure can reduce the number of face verifications by performing identity verification on the target face image set corresponding to the target terminal group. The number of images in the face image library that needs to be searched during the process can also improve the efficiency and success rate of face verification and recognition.
  • FIG. 7 is a block diagram of a face payment device according to an exemplary embodiment.
  • the face payment device 700 includes:
  • the receiving part 710 is configured to receive a face payment request sent by the target payment terminal, where the face payment request includes a face image to be verified;
  • the first determining part 720 is configured to determine the target terminal group corresponding to the target payment terminal;
  • the first verification part 730 is configured to perform identity verification on the face image to be verified based on the target face image set corresponding to the target terminal group, and obtain the first identity verification result.
  • the target face image set provides payment for the target terminal group.
  • the first operation execution part 740 is configured to, in the case where the first identity verification result indicates that the target face image set includes a target face registration image that matches the face image to be verified, based on the payment account number corresponding to the target face registration image. Perform payment operations.
  • the above device further includes:
  • the first acquisition part is configured to acquire associated business information corresponding to multiple preset payment terminals
  • the first dividing part is configured to divide the preset payment terminals corresponding to the same associated business information into the same terminal group;
  • the first construction part is configured to construct a face image set corresponding to the same terminal group based on registered face images corresponding to the same terminal group.
  • the above device further includes:
  • the second acquisition part is configured to obtain location information corresponding to multiple preset payment terminals
  • the second dividing part is configured to perform, based on location information, dividing the preset payment terminals in the preset area into the same terminal group;
  • the second construction part is configured to construct a face image set corresponding to the same terminal group based on the registered face images corresponding to the same terminal group.
  • the above device further includes:
  • the third acquisition part is configured to perform acquisition of payment operation information of multiple preset objects in the previous period of the current period, and the payment operation information represents the use of multiple preset payment terminals by the multiple preset objects in the current period. information;
  • the analysis part is configured to perform payment analysis on multiple preset objects based on payment operation information and obtain payment analysis results; the payment analysis results represent the usage probability of multiple preset objects on multiple preset payment terminals in the current cycle;
  • the second determination part is configured to determine the initial terminal group corresponding to each preset object according to the payment analysis results
  • the grouping part is configured to perform grouping of multiple preset objects based on the initial terminal group to obtain the object group;
  • the third construction part is configured to execute, based on the registered face images corresponding to the object group, construct a face image set of the terminal group corresponding to the object group.
  • the grouping part is specifically configured to divide preset objects corresponding to the same initial terminal group into the same object group.
  • the grouping part is specifically configured to divide at least two target objects among the plurality of preset objects into the same object group, and the at least two target objects include presets for the initial terminal group. A number of default objects for the same payment terminal.
  • the analysis part is specifically configured to input payment operation information into a preset payment analysis network to perform payment analysis and obtain payment analysis results.
  • the above device further includes:
  • the second verification part is configured to perform, in the case where the first identity verification result indicates that the target face image set does not include a target face registration image that matches the face image to be verified, based on the full face image set, the person to be verified is Face image is used for identity verification, and the second identity verification result is obtained;
  • the second operation execution part is configured to perform a payment operation based on the payment account corresponding to the target face registration image when the second identity verification result indicates that the entire face image set includes the target face registration image.
  • the first determining part includes:
  • the acquisition unit is configured to obtain the target terminal identification of the target payment terminal
  • a query unit configured to query a target terminal group identification including a target terminal identification from a plurality of preset terminal group identifications
  • the determining unit is configured to identify the terminal group corresponding to the target terminal group as the target terminal group.
  • FIG. 8 is a block diagram of an electronic device for face payment according to an exemplary embodiment.
  • the electronic device may be a terminal, and its internal structure diagram may be as shown in FIG. 8 .
  • the terminal may include a radio frequency (Radio Frequency, RF) circuit 810, a memory 820 including one or more computer-readable storage media, an input unit 830, a display unit 840, a sensor 850, an audio circuit 860, a wireless fidelity (Wireless) Fidelity (WiFi) module 870, a processor 880 including one or more processing cores, a power supply 890 and other components.
  • RF Radio Frequency
  • the RF circuit 810 can be used to receive and transmit information or signals during a call. In particular, after receiving the downlink information of the base station, it is handed over to one or more processors 880 for processing; in addition, the uplink data is sent to the base station. .
  • the RF circuit 810 includes, but is not limited to, an antenna, at least one amplifier, a tuner, one or more oscillators, a Subscriber Identity Module (SIM) card, a transceiver, a coupler, a low noise amplifier (Low Noise Amplifier) Amplifier, LNA), duplexer, etc.
  • SIM Subscriber Identity Module
  • the RF circuit 810 can also communicate with the network and other terminals through wireless communications.
  • the wireless communication can use any communication standard or protocol, including but not limited to Global System of Mobile communication (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), email, Short Messaging Service (SMS), etc.
  • GSM Global System of Mobile communication
  • GPRS General Packet Radio Service
  • CDMA Code Division Multiple Access
  • WCDMA Wideband Code Division Multiple Access
  • LTE Long Term Evolution
  • SMS Short Messaging Service
  • the memory 820 can be used to store software programs and modules, and the processor 880 executes various functional applications and data processing by running the software programs and modules stored in the memory 820 .
  • the memory 820 may include a stored program area and a stored data area, wherein the stored program area may store an operating system, application programs required for functions, etc.; the stored data area may store data created according to use of the terminal, etc.
  • memory 820 may include high-speed random access memory and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 820 may also include a memory controller to provide the processor 880 and the input unit 830 with access to the memory 820 .
  • the input unit 830 may be used to receive input numeric or character information, and to generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.
  • the input unit 830 may include a touch-sensitive surface 831 as well as other input devices 832 .
  • the touch-sensitive surface 831 also known as a touch display or a touchpad, can collect the user's touch operations on or near it (for example, the user uses a finger, stylus, or any suitable object or accessory on the touch-sensitive surface 831 or on the touch-sensitive surface 831). operations near the touch-sensitive surface 831), and drive the corresponding connection device according to the preset program.
  • the touch-sensitive surface 831 may include two parts: a touch detection device and a touch controller.
  • the touch detection device detects the user's touch orientation, detects the signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, converts it into contact point coordinates, and then sends it to the touch controller. to the processor 880, and can receive commands sent by the processor 880 and execute them.
  • touch-sensitive surfaces 831 can be implemented using various types such as resistive, capacitive, infrared, and surface acoustic waves.
  • the input unit 830 may also include other input devices 832.
  • other input devices 832 may include, but are not limited to, one or more of a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, a joystick, and the like.
  • the display unit 840 may be used to display information input by the user or information provided to the user as well as various graphical user interfaces of the terminal. These graphical user interfaces may be composed of graphics, text, icons, videos, and any combination thereof.
  • the display unit 840 may include a display panel 841.
  • the display panel 841 may be configured in the form of a liquid crystal display (Liquid Crystal Display, LCD), an organic light-emitting diode (OLED), etc.
  • the touch-sensitive surface 831 may cover the display panel 841.
  • the touch-sensitive surface 831 detects a touch operation on or near it, it is transmitted to the processor 880 to determine the type of touch event.
  • the processor 880 determines the type of the touch event according to The type of touch event provides corresponding visual output on display panel 841.
  • the touch-sensitive surface 831 and the display panel 841 can be two independent components to implement the input and output functions. However, in some embodiments, the touch-sensitive surface 831 and the display panel 841 can also be integrated to implement the input and output functions.
  • the terminal may also include at least one sensor 850, such as a light sensor, a motion sensor, and other sensors.
  • the light sensor may include an ambient light sensor and a proximity sensor.
  • the ambient light sensor may adjust the brightness of the display panel 841 according to the brightness of the ambient light.
  • the proximity sensor may close the display panel 841 when the terminal moves to the ear.
  • the gravity acceleration sensor can detect the magnitude of acceleration in various directions (usually three axes).
  • It can detect the magnitude and direction of gravity when stationary, and can be used to identify terminal posture applications (such as horizontal and vertical screen switching, related Games, magnetometer attitude calibration), vibration recognition related functions (such as pedometer, knock), etc.; as for the terminal, it can also be configured with other sensors such as gyroscope, barometer, hygrometer, thermometer, infrared sensor, etc.
  • the audio circuit 860, speaker 861, and microphone 862 can provide an audio interface between the user and the terminal.
  • the audio circuit 860 can transmit the electrical signal converted from the received audio data to the speaker 861, and the speaker 861 converts it into a sound signal for output; on the other hand, the microphone 862 converts the collected sound signal into an electrical signal, and the audio circuit 860 After receiving, it is converted into audio data, and then processed by the audio data output processor 880, and then sent to, for example, another terminal through the RF circuit 810, or the audio data is output to the memory 820 for further processing.
  • Audio circuitry 860 may also include an earphone jack to provide communication of peripheral earphones with the terminal.
  • WiFi is a short-distance wireless transmission technology.
  • the terminal can help users send and receive emails, browse web pages, access streaming media, etc. through the WiFi module 870. It provides users with wireless broadband Internet access.
  • FIG. 8 shows the WiFi module 870, it can be understood that it is not a necessary component of the terminal and can be omitted as needed without changing the essence of the disclosed embodiments.
  • the processor 880 is the control center of the terminal, using various interfaces and lines to connect various parts of the entire terminal, by running or executing at least one of the software programs and modules stored in the memory 820, and calling the software stored in the memory 820.
  • the data in the terminal is used to perform various functions of the terminal and process data, thereby monitoring the terminal as a whole.
  • the processor 880 may include one or more processing cores; in some embodiments, the processor 880 may integrate an application processor and a modem processor, where the application processor may process the operating system, user interface, and applications, etc., the modem processor can handle wireless communications. It can be understood that the above modem processor may not be integrated into the processor 880 .
  • the terminal also includes a power supply 890 (such as a battery) that supplies power to various components.
  • the power supply can be logically connected to the processor 880 through a power management system, thereby managing charging, discharging, and power consumption through the power management system. Management and other functions.
  • Power supply 890 may also include one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, power status indicators, and other arbitrary components.
  • the terminal may also include a camera, a Bluetooth module, and the like.
  • the display unit of the terminal is a touch screen display, and the terminal also includes a memory and one or more programs, wherein the one or more programs are stored in the memory and configured to be processed by one or more processors Execute the instructions in the method embodiments of the present disclosure.
  • an electronic device including: a processor; a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement implementations as described in the present disclosure. Face payment method in the example.
  • a computer-readable storage medium is also provided, which when instructions in the storage medium are executed by a processor of an electronic device, enables the electronic device to execute the face payment method in the embodiment of the present disclosure.
  • a computer program product containing instructions is also provided, which when run on a computer causes the computer to execute the face payment method in the embodiment of the present disclosure.
  • a computer program including computer readable code is also provided.
  • the computer readable code is run in an electronic device, a processor in the electronic device executes for implementing any of the above.
  • a facial payment method is also provided.
  • a computer program product containing instructions is provided.
  • the computer program product is used to store computer-readable instructions. When the instructions are executed, they cause the computer to perform any of the above facial payment methods.
  • the user information including but not limited to user equipment information, user personal information, etc.
  • data including but not limited to data for display, analysis data, etc.
  • user permission or consent needs to be obtained, and the collection, use and processing of relevant data need to comply with relevant laws, regulations and standards of relevant countries and regions.
  • Non-volatile memory can include read-only memory (Read-Only Memory, ROM), programmable ROM (Programmable Read Only Memory, PROM), electrically programmable ROM (Electrical Programmable Read Only Memory, EPROM), electrically erasable memory Programming ROM (Electrically Erasable Programmable Read-Only Memory, EEPROM) or flash memory. Volatile memory may include random access memory (Random Access Memory, RAM) or external cache memory.
  • RAM Random Access Memory
  • RAM is available in many forms, such as Static Random-Access Memory (SRAM), Dynamic Random-Access Memory (DRAM), Synchronous Dynamic Random-Access Memory (Synchronous Dynamic Random-Access Memory, SDRAM), Double Data Rate SDRAM (Double Data Rate SDRAM, DDRSDRAM), Enhanced SDRAM (Enhanced SDRAM, ESDRAM), Synchronous Link DRAM (Synchlink DRAM, SLDRAM), Memory Bus (Rambus) Direct RAM (RDRAM), direct memory bus dynamic RAM (Direct Rambus DRAM, DRDRAM), and memory bus dynamic RAM (Rambus DRAM, RDRAM), etc.
  • SRAM Static Random-Access Memory
  • DRAM Dynamic Random-Access Memory
  • SDRAM Synchronous Dynamic Random-Access Memory
  • SDRAM Double Data Rate SDRAM
  • Double Data Rate SDRAM Double Data Rate SDRAM
  • DDRSDRAM Double Data Rate SDRAM
  • Enhanced SDRAM Enhanced SDRAM
  • Synchronous Link DRAM Synchronous Link DRAM
  • SLDRAM Synchronous Link DRAM

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Abstract

本公开关于一种人脸支付方法、装置、电子设备、存储介质、程序和产品，该方法包括接收目标支付终端发送的人脸支付请求，人脸支付请求包括待验证人脸图像；确定目标支付终端所属的目标终端群组；基于目标终端群组对应的目标人脸图像集，对待验证人脸图像进行身份验证，得到第一身份验证结果，目标人脸图像集为目标终端群组提供支付服务的目标对象群组的注册人脸图像集；在第一身份验证结果指示目标人脸图像集包括与待验证人脸图像匹配的目标人脸注册图像的情况下，基于目标人脸注册图像对应的支付账号执行支付操作。

Description

人脸支付方法、装置、电子设备、存储介质、程序和产品
相关申请的交叉引用
本申请基于申请号为202210269526.4、申请日为2022年3月18日，名称为“人脸支付方法、装置、电子设备及存储介质”的中国专利申请提出，并要求该中国专利申请的优先权，该中国专利申请的全部内容在此引入本申请作为参考。
技术领域
本公开涉及互联网技术领域，涉及但不限于一种人脸支付方法、装置、电子设备、存储介质、计算机程序和计算机程序产品。
背景技术
随着互联网技术的发展，基于互联网进行支付的方式已经非常普及，例如，扫码支付、指纹支付和人脸支付。其中，人脸支付由于用户不用携带自身的移动设备的良好体验而得以广泛关注。
相关技术中，在进行人脸支付过程中，会将待验证人脸图像与支付系统的全量人脸图像库进行比对；但随着人脸支付系统的使用用户不断增加，预存的注册用户人脸底图的数量级越来越大，带来人脸识别验证效率和成功率较低，以及人脸支付响应速度慢等问题。
发明内容
本公开实施例提供一种人脸支付方法、装置、电子设备、存储介质、程序和产品，可以提升人脸识别验证效率和成功率，进而有效提升人脸支付响应速度。本公开实施例的技术方案如下：
根据本公开实施例的一方面，提供一种人脸支付方法，包括：
接收目标支付终端发送的人脸支付请求，所述人脸支付请求包括待验证人脸图像；
确定所述目标支付终端所属的目标终端群组；
基于所述目标终端群组对应的目标人脸图像集，对所述待验证人脸图像进行身份验证，得到第一身份验证结果，所述目标人脸图像集为所述目标终端群组提供支付服务的目标对象群组的注册人脸图像集；
在所述第一身份验证结果指示所述目标人脸图像集包括与所述待验证人脸图像匹配的目标人脸注册图像的情况下，基于所述目标人脸注册图像对应的支付账号执行支付操作。
上述技术方案，在人脸支付处理过程中，通过确定人脸支付请求对应目标支付终端所属的目标终端群组，并按终端群组来划分支付终端提供支付服务的注册人脸图像集，可以有效降低人脸验证识别的数据量，提升人脸验证识别的效率和成功率，进而也可以有效提升人脸支付响应速度。
在一个可选的实施例中，所述方法还包括：
获取多个预设支付终端对应的关联业务信息；
将同一关联业务信息对应的预设支付终端，划分到同一终端群组；
基于所述同一终端群组对应的注册人脸图像，构建所述同一终端群组对应的人脸图像集。
上述技术方案，结合支付终端对应的关联业务信息，来进行终端群组的划分，可以基于相同关联业务信息，往往面向相同用户群组的属性，大大提升终端群组中支付终端的用户重合度，进而可以提升终端群组中的支付终端共享相同的人脸图像集的概率，有 效提升人脸图像识别验证效率和成功率。
在一个可选的实施例中，所述方法还包括：
获取多个预设支付终端对应的位置信息；
基于所述位置信息，将在预设区域内的预设支付终端，划分到同一终端群组；
基于所述同一终端群组对应的注册人脸图像，构建所述同一终端群组对应的人脸图像集。
上述技术方案，结合支付终端对应的位置信息，来进行终端群组的划分，可以基于同一区域，往往面向相同用户群组的属性，大大提升终端群组中支付终端的用户重合度，进而可以提升终端群组中的支付终端共享相同的人脸图像集的概率，有效提升人脸图像识别验证效率和成功率。
在一个可选的实施例中，所述方法还包括：
获取多个预设对象在当前周期的上一周期内的支付操作信息，所述支付操作信息表征所述多个预设对象在所述当前周期内对多个预设支付终端的使用信息；
基于所述支付操作信息对所述多个预设对象进行支付分析，得到支付分析结果；所述支付分析结果表征所述多个预设对象在所述当前周期内对多个预设支付终端的使用概率；
根据所述支付分析结果，确定每个所述预设对象对应的初始终端群组；
基于所述初始终端群组对所述多个预设对象进行分组，得到对象群组；
基于所述对象群组对应的注册人脸图像，构建所述对象群组对应的终端群组的人脸图像集。
上述技术方案，对按周期获取的支付操作信息进行预设对象的支付分析，可以有效提升确定出的支付分析结果对对象的支付终端使用情况的表征精准性，进而可以更好的提升确定出的终端群组中支付终端的用户重合度和终端群组中的支付终端共享相同的人脸图像集的概率，以便有效提升人脸支付处理过程中人脸图像识别验证效率和成功率。
在一个可选的实施例中，所述基于所述初始终端群组对所述多个预设对象进行分组，得到对象群组包括：
将相同初始终端群组对应的预设对象，划分到同一对象群组。
上述技术方案，将对应相同的初始终端群组的预设对象，划分到一个对象群组，可以有效提升对应的终端群组中的支付终端共享相同的人脸图像集的概率，进而有效提升人脸图像识别验证效率和成功率。
在一个可选的实施例中，所述基于所述初始终端群组对所述多个预设对象进行分组，得到对象群组包括：
将所述多个预设对象中的至少两个目标对象，划分到同一对象群组，所述至少两个目标对象为所述初始终端群组包括的预设数量个相同支付终端的预设对象。
上述技术方案，将对应的初始终端群组中，有预设数量个相同的支付终端，划分到一个对象群组，可以有效提升对应的终端群组中的支付终端共享相同的人脸图像集的概率，进而有效提升人脸图像识别验证效率和成功率。
在一个可选的实施例中，所述基于所述支付操作信息对所述多个预设对象进行支付分析，得到支付分析结果包括：
将所述支付操作信息输入预设支付分析网络进行支付分析，得到所述支付分析结果。
上述技术方案，结合预设支付分析网络来进行支付分析，可以提升对多个预设对象对多个预设支付终端使用概率的预测精准性，进而提升支付分析的有效性。
在一个可选的实施例中，所述方法还包括：
在所述第一身份验证结果指示所述目标人脸图像集未包括与所述待验证人脸图像匹配的目标人脸注册图像的情况下，基于全量人脸图像集，对所述待验证人脸图像进行身 份验证，得到第二身份验证结果；
在所述第二身份验证结果指示所述全量人脸图像集包括所述目标人脸注册图像的情况下，基于所述目标人脸注册图像对应的支付账号执行支付操作。
上述技术方案，在第一身份验证结果指示目标人脸图像集未包括与待验证人脸图像匹配的目标人脸注册图像的情况下，结合全量人脸图像集，对待验证人脸图像进行身份验证，可以有效提升人脸支付处理过程中人脸支付验证的成功率。
在一个可选的实施例中，所述确定所述目标支付终端所属的目标终端群组包括：
获取所述目标支付终端的目标终端标识；
从多个预设终端群组标识中，查询包括所述目标终端标识的目标终端群组标识；
将所述目标终端群组标识对应的终端群组，作为所述目标终端群组。
上述技术方案，从多个预设终端群组标识中，查询包括目标终端标识的目标终端群组标识，可以便于后续按群组来进行人脸验证，进而可以有效提升人脸支付处理过程中人脸图像识别验证效率和成功率。
根据本公开实施例的另一方面，提供一种人脸支付装置，包括：
接收部分，被配置为执行接收目标支付终端发送的人脸支付请求，所述人脸支付请求包括待验证人脸图像；
第一确定部分，被配置为执行确定所述目标支付终端对应的目标终端群组；
第一验证部分，被配置为执行基于所述目标终端群组对应的目标人脸图像集，对所述待验证人脸图像进行身份验证，得到第一身份验证结果，所述目标人脸图像集为所述目标终端群组提供支付服务的目标对象群组的注册人脸图像集；
第一操作执行部分，被配置为执行在所述第一身份验证结果指示所述目标人脸图像集包括与所述待验证人脸图像匹配的目标人脸注册图像的情况下，基于所述目标人脸注册图像对应的支付账号执行支付操作。
在一个可选的实施例中，所述装置还包括：
第一获取部分，被配置为执行获取多个预设支付终端对应的关联业务信息；
第一划分部分，被配置为执行将同一关联业务信息对应的预设支付终端，划分到同一终端群组；
第一构建部分，被配置为执行基于所述同一终端群组对应的注册人脸图像，构建所述同一终端群组对应的人脸图像集。
在一个可选的实施例中，所述装置还包括：
第二获取部分，被配置为执行获取多个预设支付终端对应的位置信息；
第二划分部分，被配置为执行基于所述位置信息，将在预设区域内的预设支付终端，划分到同一终端群组；
第二构建部分，被配置为执行基于所述同一终端群组对应的注册人脸图像，构建所述同一终端群组对应的人脸图像集。
在一个可选的实施例中，所述装置还包括：
第三获取部分，被配置为执行获取多个预设对象在当前周期的上一周期内的支付操作信息，所述支付操作信息表征所述多个预设对象在所述当前周期内对多个预设支付终端的使用信息；
分析部分，被配置为执行基于所述支付操作信息对所述多个预设对象进行支付分析，得到支付分析结果；所述支付分析结果表征所述多个预设对象在所述当前周期内对多个预设支付终端的使用概率；
第二确定部分，被配置为执行根据所述支付分析结果，确定每个所述预设对象对应的初始终端群组；
分组部分，被配置为执行基于所述初始终端群组对所述多个预设对象进行分组，得 到对象群组；
第三构建部分，被配置为执行基于所述对象群组对应的注册人脸图像，构建所述对象群组对应的终端群组的人脸图像集。
在一个可选的实施例中，所述分组部分具体被配置为执行将相同初始终端群组对应的预设对象，划分到同一对象群组。
在一个可选的实施例中，所述分组部分具体被配置为执行将所述多个预设对象中的至少两个目标对象，划分到同一对象群组，所述至少两个目标对象为初始终端群组包括的预设数量个相同支付终端的预设对象。
在一个可选的实施例中，所述分析部分具体被配置为执行将所述支付操作信息输入预设支付分析网络进行支付分析，得到所述支付分析结果。
在一个可选的实施例中，所述装置还包括：
第二验证部分，被配置为执行在所述第一身份验证结果指示所述目标人脸图像集未包括与所述待验证人脸图像匹配的目标人脸注册图像的情况下，基于全量人脸图像集，对所述待验证人脸图像进行身份验证，得到第二身份验证结果；
第二操作执行部分，被配置为执行在所述第二身份验证结果指示所述全量人脸图像集包括所述目标人脸注册图像的情况下，基于所述目标人脸注册图像对应的支付账号执行支付操作。
在一个可选的实施例中，所述第一确定部分包括：
获取单元，被配置为执行获取所述目标支付终端的目标终端标识；
查询单元，被配置为执行从多个预设终端群组标识中，查询包括所述目标终端标识的目标终端群组标识；
确定单元，被配置为执行将所述目标终端群组标识对应的终端群组，作为所述目标终端群组。
根据本公开实施例的另一方面，提供一种电子设备，包括：处理器；用于存储所述处理器可执行指令的存储器；其中，所述处理器被配置为执行所述指令，以实现如上述第任一项所述的方法。
根据本公开实施例的另一方面，提供一种计算机可读存储介质，当所述存储介质中的指令由电子设备的处理器执行时，使得所述电子设备能够执行本公开实施例的上述任一所述方法。
根据本公开实施例的另一方面，提供一种包含计算机可读代码的计算机程序，当所述计算机可读代码在电子设备中运行时，所述电子设备中的处理器执行用于实现上述任一所述方法。
根据本公开实施例的另一方面，提供一种包含指令的计算机程序产品，该计算机程序产品用于存储计算机可读指令，当所述指令被执行时使得计算机执行上述任一所述方法。
应当理解的是，以上的一般描述和后文的细节描述仅是示例性和解释性的，并不能限制本公开。
附图说明
此处的附图被并入说明书中并构成本说明书的一部分，示出了符合本公开的实施例，并与说明书一起用于解释本公开实施例的原理，并不构成对本公开实施例的不当限定。
图1是根据一示例性实施例示出的一种人脸支付方法的应用环境的示意图；
图2是根据一示例性实施例示出的一种人脸支付方法的流程图；
图3是根据一示例性实施例示出的一种对支付终端分组和构建同一终端群组对应的人脸图像集的流程图；
图4是根据一示例性实施例示出的另一种对支付终端分组和构建同一终端群组对应的人脸图像集的流程图；
图5是根据一示例性实施例示出的一种对支付终端分组和构建同一终端群组对应的人脸图像集的流程图；
图6是根据一示例性实施例示出的一种对支付终端分组和构建同一终端群组对应的人脸图像集的流程图；
图7是根据一示例性实施例示出的一种人脸支付装置框图；
图8是根据一示例性实施例示出的一种用于人脸支付的电子设备的框图。
具体实施方式
为了使本领域普通人员更好地理解本公开的技术方案，下面将结合附图，对本公开实施例中的技术方案进行清楚、完整地描述。
需要说明的是，本公开实施例的说明书和权利要求书及上述附图中的术语“第一”、“第二”等是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。应该理解这样使用的数据在适当情况下可以互换，以便这里描述的本公开的实施例能够以除了在这里图示或描述的那些以外的顺序实施。以下示例性实施例中所描述的实施方式并不代表与本公开相一致的所有实施方式。相反，它们仅是与如所附权利要求书中所详述的、本公开实施例的一些方面相一致的装置和方法的例子。
在相关技术中，相较于统的现金支付以及其它电子支付手段，人脸支付的优点在于不需要携带任何实物、可以提升购物的整体体验。请参阅图1，图1是根据一示例性实施例示出的一种人脸支付方法的应用环境的示意图，如图1所示，该应用环境可以包括支付终端100和服务器200。
在一个可选的实施例中，支付终端100可以为用于面向任一用户受理人脸支付的终端。例如，支付终端100可以为实体电子设备，也可以为运行于上述实体电子设备的软体，例如应用程序等。示例性地，支付终端100可以设置有预设摄像头，可选的，该预设摄像头可以为与支付终端一体的摄像头，也可以为通过有线或无线的方式连接的分体式摄像头。
在一个可选的实施例中，服务器200可以为支付终端100提供后台服务，结合支付终端采集的人脸图像进行人脸支付处理。例如，服务器200可以是独立的物理服务器，也可以是多个物理服务器构成的服务器集群或者分布式系统。
此外，需要说明的是，图1所示的仅仅是本公开实施例提供的一种应用环境，在实际应用中，还可以包括其他应用环境，例如可以包括预先用于进行人脸注册的移动终端等。
本说明书实施例中，上述支付终端100以及服务器200可以通过有线或无线通信方式进行直接或间接地连接，本公开实施例在此不做限制。
图2是根据一示例性实施例示出的一种人脸支付方法的流程图，该人脸支付方法可以应用于服务器，如图2所示，该方法可以包括以下步骤：
S201：接收目标支付终端发送的人脸支付请求。
在实际应用中，用户在商场、超市等实体场所购买物品需要进行结算的情况下，可以在实体场所提供的支付终端前，通过刷脸来进行所购买物品的支付。
在一个实施例中，目标支付终端可以为任一面向用户受理人脸支付的终端。上述人脸支付请求可以包括待验证人脸图像；可选的，目标支付终端在采集到待验证人脸图像的情况下，可以向服务器发送包括该待验证人脸图像的人脸支付请求，以便服务器进行人脸支付处理。
S203：确定目标支付终端所属的目标终端群组。
在一个实施例中，可以预先将支付系统中支付终端进行分组，并将同一组中的支付终端关联对同一人脸图像集，以便提升后续人脸支付处理过程中，人脸验证效率。
在一个可选的实施例中，具有共同或相似信息的支付终端，往往会受理同一用户群组中用户的人脸支付业务。可选的，上述方法还可以包括：预先对多个预设支付终端进行分组和构建同一终端群组对应的人脸图像集的步骤，示例性地，如图3所示，对多个预设支付终端进行分组和构建同一终端群组对应的人脸图像集可以包括：
S301：获取多个预设支付终端对应的关联业务信息；
S303：将同一关联业务信息对应的预设支付终端，划分到同一终端群组；
S305：基于同一终端群组对应的注册人脸图像，构建同一终端群组对应的人脸图像集。
在一个实施例中，多个预设支付终端可以为支付系统中的支付终端。关联业务信息可以为能够表征支付终端所属业务方的信息，例如业务方为某超市的情况下，关联业务信息可以为超市标识信息等，相应的，可以将相同的超市标识信息对应的预设支付终端，划分到同一终端群组。例如，在业务方表示某连锁品牌的情况下，关联业务信息可以为连锁品牌标识，相应地，可以将相同的连锁品牌标识对应的预设支付终端，划分到同一终端群组。
在一个实施例中，任一终端群组对应的注册人脸图像可以包括在该终端群组中的支付终端进行人脸支付注册的用户的注册人脸图像和在该终端群组中的支付终端使用过人脸支付的用户的注册人脸图像。
上述实施例中，结合支付终端对应的关联业务信息，来进行终端群组的划分，可以基于相同关联业务信息，往往面向相同用户群组的属性，大大提升终端群组中支付终端的用户重合度，进而可以提升终端群组中的支付终端共享相同的人脸图像集的概率，有效提升人脸图像识别验证效率和成功率。
在一个实施例中，如图4所示，对多个预设支付终端进行分组和构建同一终端群组对应的人脸图像集可以包括：
S401：获取多个预设支付终端对应的位置信息；
S403：基于位置信息，将在预设区域内的预设支付终端，划分到同一终端群组；
S405：基于同一终端群组对应的注册人脸图像，构建同一终端群组对应的人脸图像集。
在一个实施例中，多个预设支付终端对应的位置信息可以为多个预设支付终端各自所在位置的信息。示例性地，预设区域可以结合实际应用进行设置，例如预设街区、预设商圈等，或者以预设位置为圆心的预设范围内。
上述实施例中，结合支付终端对应的位置信息，来进行终端群组的划分，可以基于同一区域，往往面向相同用户群组的属性，大大提升终端群组中支付终端的用户重合度，进而可以提升终端群组中的支付终端共享相同的人脸图像集的概率，有效提升人脸图像识别验证效率和成功率。
在一个实施例中，如图5所示，对多个预设支付终端进行分组和构建同一终端群组对应的人脸图像集可以包括：
S501：获取多个预设对象在当前周期的上一周期内的支付操作信息；
在一个实施例中，多个预设对象可以为在支付系统中进行过人脸支付注册的用户账号。上述支付操作信息可以表征多个预设对象在当前周期内对多个预设支付终端的使用信息。示例性地，获取支付操作信息的周期可以结合实际应用需求进行设置，例如一周、二周等。
S503：基于支付操作信息对多个预设对象进行支付分析，得到支付分析结果；
在一个实施例中，上述支付分析结果可以表征多个预设对象在当前周期内对多个预 设支付终端的使用概率。
在一个可选的实施例中，上述基于支付操作信息对多个预设对象进行支付分析，得到支付分析结果可以包括：
将支付操作信息输入预设支付分析网络进行支付分析，得到支付分析结果。
在一个实施例中，预设支付分析网络可以为预先基于样本对象在第一历史周期内的支付操作信息和样本对象对应的标注支付分析结果，对预设深度学习网络进行支付分析训练得到的。例如，该标注支付分析结果可以为样本对象在第二历史周期内对多个样本支付终端的使用概率。样本对象可以为在支付系统中进行过人脸支付注册的用户账号；第一历史周期可以为第二历史周期的上一周期；多个预设支付终端可以包括上述多个样本支付终端。可选的，样本对象对应的标注支付分析结果可以为1或0，例如，若样本对象中某一对象在第二历史周期内使用某一样本支付终端的次数大于等于预设阈值(预设阈值大于等于1)，该对象对应的标注支付分析结果可以为1；反之，若样本对象中某一对象在第二历史周期内使用某一样本支付终端的次数小于预设阈值，该对象对应的标注支付分析结果可以为0。
上述实施例中，结合预设支付分析网络来进行支付分析，可以提升对多个预设对象对多个预设支付终端使用概率的预测精准性，进而提升支付分析的有效性。
S505：根据支付分析结果，确定每个预设对象对应的初始终端群组；
在一个实施例中，上述根据支付分析结果，确定每个预设对象对应的初始终端群组可以包括：确定每个预设对象对应的支付分析结果中满足预设条件的支付分析结果对应的预设支付终端；并基于满足预设条件的支付分析结果对应的预设支付终端，构建该预设对象的初始终端群组。例如，预设条件可以为预设设置的筛选出初始终端群组的条件，可选的，以上述支付分析结果为0或1的场景为例，满足预设条件的支付分析结果可以为大于等于预设概率的支付分析结果。
S507：基于初始终端群组对多个预设对象进行分组，得到对象群组；
在一个实施例中，可以将对应相同的初始终端群组的预设对象，划分到一个对象群组，相应的，该对象群组对应的终端群组可以为该对象群组中对象对应的初始终端群组的并集(例如，由于对象群组中对象对应的初始终端群相同，相应的，对象群组对应的终端群组可以为对象群组中任一对象对应的初始终端群组)；相应的，上述基于初始终端群组对多个预设对象进行分组，得到对象群组可以包括：
将相同初始终端群组对应的预设对象，划分到同一对象群组。
上述实施例中，将对应相同的初始终端群组的预设对象，划分到一个对象群组，可以有效提升对应的终端群组中的支付终端共享相同的人脸图像集的概率，进而有效提升人脸图像识别验证效率和成功率。
在另一个可选的实施例中，可以将对应的初始终端群组中，有预设数量个相同的支付终端，划分到一个对象群组，相应的，后续这个对象群组对应的终端群组，可以为这个对象群组中预设对象对应初始终端群组的并集。相应的，上述基于终端群组对多个预设对象进行分组，得到对象群组可以包括：
将多个预设对象中的至少两个目标对象，划分到同一对象群组。
在一个实施例中，上述至少两个目标对象可以为多个预设对象中对应的初始终端群组包括的预设数量个相同支付终端的预设对象。
上述实施例中，将对应的初始终端群组中，有预设数量个相同的支付终端，划分到一个对象群组，可以有效提升对应的终端群组中的支付终端共享相同的人脸图像集的概率，进而有效提升人脸图像识别验证效率和成功率。
S509：基于对象群组对应的注册人脸图像，构建对象群组对应的终端群组的人脸图像集。
在一个实施例中，对象群组对应的注册人脸图像可以为该对象群组中对象的注册人脸图像；相应的，可以将一个对象群组中对象的注册人脸图像作为该对象群组对应的终端群组的人脸图像集。
上述实施例中，对按周期获取的支付操作信息进行预设对象的支付分析，可以有效提升确定出的支付分析结果对对象的支付终端使用情况的表征精准性，进而可以更好的提升确定出的终端群组中支付终端的用户重合度和终端群组中的支付终端共享相同的人脸图像集的概率，以便有效提升人脸支付处理过程中人脸图像识别验证效率和成功率。
在另一个可选的实施例中，如图6所示，对多个预设支付终端进行分组和构建同一终端群组对应的人脸图像集可以包括：
S601：获取多个预设对象在当前周期的上一周期内的支付操作信息；
S603：根据每个预设对象在上一周期内的支付操作信息，确定每个预设对象在上一周期内对每个预设支付终端的使用次数；
S605：基于使用次数，确定每个预设对象的关联终端群组；
S607：基于关联终端群组对多个预设对象进行分组，得到对象群组；
S609：基于对象群组对应的注册人脸图像，构建对象群组对应的终端群组的人脸图像集。
在一个实施例中，上述基于使用次数，确定每个预设对象的关联终端群组可以包括针对每个预设对象，将预设对象对多个预设支付终端对应使用次数与预设次数进行比较，若某一预设支付终端对应的使用次数大于等于预设次数，可以基于使用次数大于等于预设次数的预设支付终端，构建该预设对象的关联终端群组。
在一个可选的实施例中，可以将对应相同的关联终端群组的预设对象，划分到一个对象群组，相应的，上述基于关联终端群组对多个预设对象进行分组，得到对象群组可以包括：将相同关联终端群组对应的预设对象，划分到同一对象群组。
在另一个可选的实施例中，可以将对应的关联终端群组中，有预设数量个相同的支付终端，划分到一个对象群组，相应的，后续这个对象群组对应的终端群组，可以为这个对象群组中预设对象对应关联终端群组的并集。相应的，上述基于终端群组对多个预设对象进行分组，得到对象群组可以包括：将多个预设对象中的至少两个目标对象，划分到同一对象群组，至少两个目标对象可以为关联终端群组包括预设数量个相同支付终端的预设对象。
上述实施例中，按周期来获取支付操作信息，可以有效提升支付操作信息的时效性和有效性，进而可以更好的提升确定出的终端群组中支付终端的用户重合度和终端群组中的支付终端共享相同的人脸图像集的概率，以便有效提升人脸支付处理过程中人脸图像识别验证效率和成功率。
在一个可选的实施例中，在确定出终端群组的情况下，可以创建每个终端群组对应的预设终端群组标识，例如，该预设终端群组标识可以包括终端群组中每个支付终端的终端标识。可选的，上述预设终端群组标识信息可以存储到预设的数据库中，以便后续查询。
在一个可选的实施例中，上述确定目标支付终端所属的目标终端群组包括：获取目标支付终端的目标终端标识；从多个预设终端群组标识中，查询包括目标终端标识的目标终端群组标识；将目标终端群组标识对应的终端群组，作为目标终端群组。
上述实施例中，从多个预设终端群组标识中，查询包括目标终端标识的目标终端群组标识，可以便于后续按群组来进行人脸验证，有效降低了人脸验证过程中需要搜索的人脸图像库的图像数量，即，降低了人脸验证过程中的数据处理量，进而可以有效提升人脸支付处理过程中人脸图像识别验证效率和成功率。
S205：基于目标终端群组对应的目标人脸图像集，对待验证人脸图像进行身份验证， 得到第一身份验证结果。
在一个实施例中，上述目标人脸图像集可以为目标终端群组提供支付服务(即受理人脸支付业务)的目标对象群组的注册人脸图像集；
在一个可选的实施例中，可以获取目标人脸图像集中每一人脸图像的人脸图像特征和待验证人脸图像的待验证人脸图像特征；接着，可以确定目标人脸图像集中每一人脸图像的人脸图像特征和待验证人脸图像特征间的相似度；可选的，若最大相似度大于等于预设相似度阈值，可以得到指示目标人脸图像集包括与待验证人脸图像匹配的目标人脸注册图像的第一身份验证结果；反之，若最大相似度小于预设相似度阈值，可以得到指示目标人脸图像集未包括目标人脸注册图像的第一身份验证结果。
在一个可选的实施例中，人脸图像特征间的相似度可以包括但不限于人脸图像特征间的欧式距离、曼哈顿距离等。
S207：在第一身份验证结果指示目标人脸图像集包括与待验证人脸图像匹配的目标人脸注册图像的情况下，基于目标人脸注册图像对应的支付账号执行支付操作。
在一个实施例中，上述人脸支付请求还可以包括支付信息，例如，该支付信息可以为需要消耗的虚拟资源量，相应的，在第一身份验证结果指示目标人脸图像集包括与待验证人脸图像匹配的目标人脸注册图像的情况下，可以从目标人脸注册图像对应的支付账号中扣除对应的虚拟资源量，以实现支付操作的执行。
由以上本说明书实施例提供的技术方案可见，本说明书中在人脸支付处理过程中，通过确定人脸支付请求对应目标支付终端所属的目标终端群组，并按终端群组来划分支付终端提供支付服务的注册人脸图像集，可以有效降低人脸验证识别的数据量，同时，通过在目标人脸图像集中针对性地进行人脸验证，可以提升人脸验证识别的效率和成功率，进而也可以有效提升人脸支付响应速度。
在一个可选的实施例中，上述方法还可以包括：
在第一身份验证结果指示目标人脸图像集未包括与待验证人脸图像匹配的目标人脸注册图像的情况下，基于全量人脸图像集，对待验证人脸图像进行身份验证，得到第二身份验证结果。
在第二身份验证结果指示全量人脸图像集包括目标人脸注册图像的情况下，基于目标人脸注册图像对应的支付账号执行支付操作。
在一个实施例中，全量人脸图像集可以为支付系统中全部的注册人脸图像。例如，基于全量人脸图像集，对待验证人脸图像进行身份验证，得到第二身份验证结果可以参见上述基于目标终端群组对应的目标人脸图像集，对待验证人脸图像进行身份验证，得到第一身份验证结果的具体细化。
上述实施例中，在第一身份验证结果指示目标人脸图像集未包括与待验证人脸图像匹配的目标人脸注册图像的情况下，结合全量人脸图像集，对待验证人脸图像进行身份验证，可以有效提升人脸支付处理过程中人脸支付验证的成功率。
本公开实施例可以应用于零售商店、超市等人脸密集的支付场景中，也可以应用于智能便利店、无人售货机、无人便利店等任何需要进行人脸支付的场景中；与相关技术中需要在包括海量人脸图像的全量人脸图像集中进行人脸验证的方案相比，本公开实施例通过在目标终端群组对应的目标人脸图像集进行身份验证，可以降低人脸验证过程中需要搜索的人脸图像库的图像数量，同时可以提升人脸验证识别的效率和成功率。
图7是根据一示例性实施例示出的一种人脸支付装置框图。参照图7，该人脸支付装置700包括：
接收部分710，被配置为接收目标支付终端发送的人脸支付请求，人脸支付请求包括待验证人脸图像；
第一确定部分720，被配置为确定目标支付终端对应的目标终端群组；
第一验证部分730，被配置为基于目标终端群组对应的目标人脸图像集，对待验证人脸图像进行身份验证，得到第一身份验证结果，目标人脸图像集为目标终端群组提供支付服务的目标对象群组的注册人脸图像集；
第一操作执行部分740，被配置为在第一身份验证结果指示目标人脸图像集包括与待验证人脸图像匹配的目标人脸注册图像的情况下，基于目标人脸注册图像对应的支付账号执行支付操作。
在一个可选的实施例中，上述装置还包括：
第一获取部分，被配置为执行获取多个预设支付终端对应的关联业务信息；
第一划分部分，被配置为执行将同一关联业务信息对应的预设支付终端，划分到同一终端群组；
第一构建部分，被配置为执行基于同一终端群组对应的注册人脸图像，构建同一终端群组对应的人脸图像集。
在一个可选的实施例中，上述装置还包括：
第二获取部分，被配置为执行获取多个预设支付终端对应的位置信息；
第二划分部分，被配置为执行基于位置信息，在预设区域内的预设支付终端，划分到同一终端群组；
第二构建部分，被配置为执行基于同一终端群组对应的注册人脸图像，构建同一终端群组对应的人脸图像集。
在一个可选的实施例中，上述装置还包括：
第三获取部分，被配置为执行获取多个预设对象在当前周期的上一周期内的支付操作信息，支付操作信息表征多个预设对象在当前周期内对多个预设支付终端的使用信息；
分析部分，被配置为执行基于支付操作信息对多个预设对象进行支付分析，得到支付分析结果；支付分析结果表征多个预设对象在当前周期内对多个预设支付终端的使用概率；
第二确定部分，被配置为执行根据支付分析结果，确定每个预设对象对应的初始终端群组；
分组部分，被配置为执行基于初始终端群组对多个预设对象进行分组，得到对象群组；
第三构建部分，被配置为执行基于对象群组对应的注册人脸图像，构建对象群组对应的终端群组的人脸图像集。
在一个可选的实施例中，分组部分具体被配置为执行将相同初始终端群组对应的预设对象，划分到同一对象群组。
在一个可选的实施例中，分组部分具体被配置为执行将多个预设对象中的至少两个目标对象，划分到同一对象群组，至少两个目标对象为初始终端群组包括预设数量个相同支付终端的预设对象。
在一个可选的实施例中，分析部分具体被配置为执行将支付操作信息输入预设支付分析网络进行支付分析，得到支付分析结果。
在一个可选的实施例中，上述装置还包括：
第二验证部分，被配置为执行在第一身份验证结果指示目标人脸图像集未包括与待验证人脸图像匹配的目标人脸注册图像的情况下，基于全量人脸图像集，对待验证人脸图像进行身份验证，得到第二身份验证结果；
第二操作执行部分，被配置为执行在第二身份验证结果指示全量人脸图像集包括目标人脸注册图像的情况下，基于目标人脸注册图像对应的支付账号执行支付操作。
在一个可选的实施例中，第一确定部分包括：
获取单元，被配置为执行获取目标支付终端的目标终端标识；
查询单元，被配置为执行从多个预设终端群组标识中，查询包括目标终端标识的目标终端群组标识；
确定单元，被配置为执行将目标终端群组标识对应的终端群组，作为目标终端群组。
关于上述实施例中的装置，其中各个部分执行操作的具体方式已经在有关该方法的实施例中进行了详细描述，此处将不做详细阐述说明。
图8是根据一示例性实施例示出的一种用于人脸支付的电子设备的框图，该电子设备可以是终端，其内部结构图可以如图8所示。所述终端可以包括射频(Radio Frequency，RF)电路810、包括有一个或一个以上计算机可读存储介质的存储器820、输入单元830、显示单元840、传感器850、音频电路860、无线保真(Wireless Fidelity，WiFi)模块870、包括有一个或者一个以上处理核心的处理器880、以及电源890等部件。本领域技术人员可以理解，图8中示出的终端结构并不构成对终端的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。其中：
RF电路810可用于收发信息或通话过程中，信号的接收和发送，特别地，将基站的下行信息接收后，交由一个或者一个以上处理器880处理；另外，将涉及上行的数据发送给基站。通常，RF电路810包括但不限于天线、至少一个放大器、调谐器、一个或多个振荡器、用户身份模块(Subscriber Identity Module，SIM)卡、收发信机、耦合器、低噪声放大器(Low Noise Amplifier，LNA)、双工器等。此外，RF电路810还可以通过无线通信与网络和其他终端通信。所述无线通信可以使用任一通信标准或协议，包括但不限于全球移动通讯系统(Global System of Mobile communication，GSM)、通用分组无线服务(General Packet Radio Service，GPRS)、码分多址(Code Division Multiple Access，CDMA)、宽带码分多址(Wideband Code Division Multiple Access,WCDMA)、长期演进(Long Term Evolution,LTE)、电子邮件、短消息服务(Short Messaging Service，SMS)等。
存储器820可用于存储软件程序以及模块，处理器880通过运行存储在存储器820的软件程序以及模块，从而执行各种功能应用以及数据处理。存储器820可包括存储程序区和存储数据区，其中，存储程序区可存储操作系统、功能所需的应用程序等；存储数据区可存储根据所述终端的使用所创建的数据等。此外，存储器820可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件、闪存器件、或其他易失性固态存储器件。相应地，存储器820还可以包括存储器控制器，以提供处理器880和输入单元830对存储器820的访问。
输入单元830可用于接收输入的数字或字符信息，以及产生与用户设置以及功能控制有关的键盘、鼠标、操作杆、光学或者轨迹球信号输入。例如，输入单元830可包括触敏表面831以及其他输入设备832。触敏表面831，也称为触摸显示屏或者触控板，可收集用户在其上或附近的触摸操作(比如用户使用手指、触笔等任何适合的物体或附件在触敏表面831上或在触敏表面831附近的操作)，并根据预先设定的程式驱动相应的连接装置。可选的，触敏表面831可包括触摸检测装置和触摸控制器两个部分。其中，触摸检测装置检测用户的触摸方位，并检测触摸操作带来的信号，将信号传送给触摸控制器；触摸控制器从触摸检测装置上接收触摸信息，并将它转换成触点坐标，再送给处理器880，并能接收处理器880发来的命令并加以执行。此外，可以采用电阻式、电容式、红外线以及表面声波等多种类型实现触敏表面831。除了触敏表面831，输入单元830还可以包括其他输入设备832。例如，其他输入设备832可以包括但不限于物理键盘、功能键(比如音量控制按键、开关按键等)、轨迹球、鼠标、操作杆等中的一种或多种。显示单元840可用于显示由用户输入的信息或提供给用户的信息以及所述终端的各种图形用户接口，这些图形用户接口可以由图形、文本、图标、视频和其任意组合来构成。显示单元840可包括显示面板841，可选的，可以采用液晶显示器(Liquid Crystal Display， LCD)、有机发光二极管(Organic Light-Emitting Diode,OLED)等形式来配置显示面板841。在一些实施例中，触敏表面831可覆盖显示面板841，当触敏表面831检测到在其上或附近的触摸操作后，传送给处理器880以确定触摸事件的类型，随后处理器880根据触摸事件的类型在显示面板841上提供相应的视觉输出。其中，触敏表面831与显示面板841可以两个独立的部件来实现输入和输入功能，但是在某些实施例中，也可以将触敏表面831与显示面板841集成而实现输入和输出功能。
所述终端还可包括至少一种传感器850，比如光传感器、运动传感器以及其他传感器。例如，光传感器可包括环境光传感器及接近传感器，其中，环境光传感器可根据环境光线的明暗来调节显示面板841的亮度，接近传感器可在所述终端移动到耳边时，关闭显示面板841和背光中的至少一项。作为运动传感器的一种，重力加速度传感器可检测各个方向上(一般为三轴)加速度的大小，静止时可检测出重力的大小及方向，可用于识别终端姿态的应用(比如横竖屏切换、相关游戏、磁力计姿态校准)、振动识别相关功能(比如计步器、敲击)等；至于所述终端还可配置的陀螺仪、气压计、湿度计、温度计、红外线传感器等其他传感器。
音频电路860、扬声器861，传声器862可提供用户与所述终端之间的音频接口。音频电路860可将接收到的音频数据转换后的电信号，传输到扬声器861，由扬声器861转换为声音信号输出；另一方面，传声器862将收集的声音信号转换为电信号，由音频电路860接收后转换为音频数据，再将音频数据输出处理器880处理后，经RF电路810以发送给比如另一终端，或者将音频数据输出至存储器820以便进一步处理。音频电路860还可能包括耳塞插孔，以提供外设耳机与所述终端的通信。
WiFi属于短距离无线传输技术，所述终端通过WiFi模块870可以帮助用户收发电子邮件、浏览网页和访问流式媒体等，它为用户提供了无线的宽带互联网访问。虽然图8示出了WiFi模块870，但是可以理解的是，其并不属于所述终端的必须构成，完全可以根据需要在不改变公开实施例的本质的范围内而省略。
处理器880是所述终端的控制中心，利用各种接口和线路连接整个终端的各个部分，通过运行或执行存储在存储器820内的软件程序和模块中的至少一项，以及调用存储在存储器820内的数据，执行所述终端的各种功能和处理数据，从而对终端进行整体监控。可选的，处理器880可包括一个或多个处理核心；在一些实施例中，处理器880可集成应用处理器和调制解调处理器，其中，应用处理器可以处理操作系统、用户界面和应用程序等，调制解调处理器可以处理无线通信。可以理解的是，上述调制解调处理器也可以不集成到处理器880中。
所述终端还包括给各个部件供电的电源890(比如电池)，在一些实施例中，电源可以通过电源管理系统与处理器880逻辑相连，从而通过电源管理系统实现管理充电、放电、以及功耗管理等功能。电源890还可以包括一个或一个以上的直流或交流电源、再充电系统、电源故障检测电路、电源转换器或者逆变器、电源状态指示器等任意组件。
尽管未示出，所述终端还可以包括摄像头、蓝牙模块等。在本实施例中，终端的显示单元是触摸屏显示器，终端还包括有存储器，以及一个或者一个以上的程序，其中一个或者一个以上程序存储于存储器中，且经配置以由一个或者一个以上处理器执行本公开中方法实施例中的指令。
在示例性实施例中，还提供了一种电子设备，包括：处理器；用于存储该处理器可执行指令的存储器；其中，该处理器被配置为执行该指令，以实现如本公开实施例中的人脸支付方法。
在示例性实施例中，还提供了一种计算机可读存储介质，当该存储介质中的指令由电子设备的处理器执行时，使得电子设备能够执行本公开实施例中的人脸支付方法。
在示例性实施例中，还提供了一种包含指令的计算机程序产品，当其在计算机上运 行时，使得计算机执行本公开实施例中的人脸支付方法。
在示例性实施例中，还提供了一种包含计算机可读代码的计算机程序，当所述计算机可读代码在电子设备中运行时，所述电子设备中的处理器执行用于实现上述任意一种人脸支付方法。
在示例性实施例中，提供一种包含指令的计算机程序产品，该计算机程序产品用于存储计算机可读指令，当所述指令被执行时使得计算机执行上述任意一种人脸支付方法。
需要说明的是，本公开实施例所涉及的用户信息(包括但不限于用户设备信息、用户个人信息等)和数据(包括但不限于用于展示的数据、分析的数据等)，当本公开以上实施例运用到具体产品或技术中时，需要获得用户许可或者同意，且相关数据的收集、使用和处理需要遵守相关国家和地区的相关法律法规和标准。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机程序来指令相关的硬件来完成，该计算机程序可存储于一非易失性计算机可读取存储介质中，该计算机程序在执行时，可包括如上述各方法的实施例的流程。其中，本公开所提供的各实施例中所使用的对存储器、存储、数据库或其它介质的任何引用，均可包括非易失性和易失性存储器中的至少一项。非易失性存储器可包括只读存储器(Read-Only Memory，ROM)、可编程ROM(Programmable Read Only Memory，PROM)、电可编程ROM(Electrical Programmable Read Only Memory，EPROM)、电可擦除可编程ROM(Electrically Erasable Programmable Read-Only Memory，EEPROM)或闪存。易失性存储器可包括随机存取存储器(Random Access Memory，RAM)或者外部高速缓冲存储器。作为说明而非局限，RAM以多种形式可得，诸如静态随机存取存储器(Static Random-Access Memory，SRAM)、动态随机存取存储器(Dynamic Random Access Memory，DRAM)、同步动态随机存取内存(Synchronous Dynamic Random-Access Memory，SDRAM)、双数据率SDRAM(Double Data Rate SDRAM，DDRSDRAM)、增强型SDRAM(Enhanced SDRAM，ESDRAM)、同步链路DRAM(Synchlink DRAM，SLDRAM)、存储器总线(Rambus)直接RAM(RDRAM)、直接存储器总线动态RAM(Direct Rambus DRAM，DRDRAM)、以及存储器总线动态RAM(Rambus DRAM，RDRAM)等。
本领域技术人员在考虑说明书及实践这里公开的方案后，将容易想到本公开的其它实施方案。本公开旨在涵盖本公开的任何变型、用途或者适应性变化，这些变型、用途或者适应性变化遵循本公开的一般性原理并包括本公开未公开的本技术领域中的公知常识或惯用技术手段。说明书和实施例仅被视为示例性的，本公开的真正范围和精神由下面的权利要求指出。
应当理解的是，本公开并不局限于上面已经描述并在附图中示出的精确结构，并且可以在不脱离其范围进行各种修改和改变。本公开的范围仅由所附的权利要求来限制。

Claims (22)

  1. 一种人脸支付方法，所述方法由电子设备执行，所述方法包括：
    接收目标支付终端发送的人脸支付请求，所述人脸支付请求包括待验证人脸图像；
    确定所述目标支付终端所属的目标终端群组；
    基于所述目标终端群组对应的目标人脸图像集，对所述待验证人脸图像进行身份验证，得到第一身份验证结果，所述目标人脸图像集为所述目标终端群组提供支付服务的目标对象群组的注册人脸图像集；
    在所述第一身份验证结果指示所述目标人脸图像集包括与所述待验证人脸图像匹配的目标人脸注册图像的情况下，基于所述目标人脸注册图像对应的支付账号执行支付操作。
  2. 根据权利要求1所述的人脸支付方法，其中，所述方法还包括：
    获取多个预设支付终端对应的关联业务信息；
    将同一关联业务信息对应的预设支付终端，划分到同一终端群组；
    基于所述同一终端群组对应的注册人脸图像，构建所述同一终端群组对应的人脸图像集。
  3. 根据权利要求1或2所述的人脸支付方法，其中，所述方法还包括：
    获取多个预设支付终端对应的位置信息；
    基于所述位置信息，将在预设区域内的预设支付终端，划分到同一终端群组；
    基于所述同一终端群组对应的注册人脸图像，构建所述同一终端群组对应的人脸图像集。
  4. 根据权利要求1至3任一项所述的人脸支付方法，其中，所述方法还包括：
    获取多个预设对象在当前周期的上一周期内的支付操作信息，所述支付操作信息表征所述多个预设对象在所述当前周期内对多个预设支付终端的使用信息；
    基于所述支付操作信息对所述多个预设对象进行支付分析，得到支付分析结果；所述支付分析结果表征所述多个预设对象在所述当前周期内对多个预设支付终端的使用概率；
    根据所述支付分析结果，确定每个所述预设对象对应的初始终端群组；
    基于所述初始终端群组对所述多个预设对象进行分组，得到对象群组；
    基于所述对象群组对应的注册人脸图像，构建所述对象群组对应的终端群组的人脸图像集。
  5. 根据权利要求4所述的人脸支付方法，其中，所述基于所述初始终端群组对所述多个预设对象进行分组，得到对象群组包括：
    将相同初始终端群组对应的预设对象，划分到同一对象群组。
  6. 根据权利要求4或5所述的人脸支付方法，其中，所述基于所述初始终端群组对所述多个预设对象进行分组，得到对象群组包括：
    将所述多个预设对象中的至少两个目标对象，划分到同一对象群组，所述至少两个目标对象为所述初始终端群组包括的预设数量个相同支付终端的预设对象。
  7. 根据权利要求4至6任一项所述的人脸支付方法，其中，所述基于所述支付操作信息对所述多个预设对象进行支付分析，得到支付分析结果包括：
    将所述支付操作信息输入预设支付分析网络进行支付分析，得到所述支付分析结果。
  8. 根据权利要求1至7任一所述的人脸支付方法，其中，所述方法还包括：
    在所述第一身份验证结果指示所述目标人脸图像集未包括与所述待验证人脸图像匹 配的目标人脸注册图像的情况下，基于全量人脸图像集，对所述待验证人脸图像进行身份验证，得到第二身份验证结果；
    在所述第二身份验证结果指示所述全量人脸图像集包括所述目标人脸注册图像的情况下，基于所述目标人脸注册图像对应的支付账号执行支付操作。
  9. 根据权利要求1至8任一所述的人脸支付方法，其中，所述确定所述目标支付终端所属的目标终端群组包括：
    获取所述目标支付终端的目标终端标识；
    从多个预设终端群组标识中，查询包括所述目标终端标识的目标终端群组标识；
    将所述目标终端群组标识对应的终端群组，作为所述目标终端群组。
  10. 一种人脸支付装置，包括：
    接收部分，被配置为执行接收目标支付终端发送的人脸支付请求，所述人脸支付请求包括待验证人脸图像；
    第一确定部分，被配置为执行确定所述目标支付终端对应的目标终端群组；
    第一验证部分，被配置为执行基于所述目标终端群组对应的目标人脸图像集，对所述待验证人脸图像进行身份验证，得到第一身份验证结果，所述目标人脸图像集为所述目标终端群组提供支付服务的目标对象群组的注册人脸图像集；
    第一操作执行部分，被配置为执行在所述第一身份验证结果指示所述目标人脸图像集包括与所述待验证人脸图像匹配的目标人脸注册图像的情况下，基于所述目标人脸注册图像对应的支付账号执行支付操作。
  11. 根据权利要求10所述的装置，其中，所述装置还包括：
    第一获取部分，被配置为执行获取多个预设支付终端对应的关联业务信息；
    第一划分部分，被配置为执行将同一关联业务信息对应的预设支付终端，划分到同一终端群组；
    第一构建部分，被配置为执行基于所述同一终端群组对应的注册人脸图像，构建所述同一终端群组对应的人脸图像集。
  12. 根据权利要求10或11所述的装置，其中，所述装置还包括：
    第二获取部分，被配置为执行获取多个预设支付终端对应的位置信息；
    第二划分部分，被配置为执行基于所述位置信息，将在预设区域内的预设支付终端，划分到同一终端群组；
    第二构建部分，被配置为执行基于所述同一终端群组对应的注册人脸图像，构建所述同一终端群组对应的人脸图像集。
  13. 根据权利要求10至12任一项所述的装置，其中，所述装置还包括：
    第三获取部分，被配置为执行获取多个预设对象在当前周期的上一周期内的支付操作信息，所述支付操作信息表征所述多个预设对象在所述当前周期内对多个预设支付终端的使用信息；
    分析部分，被配置为执行基于所述支付操作信息对所述多个预设对象进行支付分析，得到支付分析结果；所述支付分析结果表征所述多个预设对象在所述当前周期内对多个预设支付终端的使用概率；
    第二确定部分，被配置为执行根据所述支付分析结果，确定每个所述预设对象对应的初始终端群组；
    分组部分，被配置为执行基于所述初始终端群组对所述多个预设对象进行分组，得到对象群组；
    第三构建部分，被配置为执行基于所述对象群组对应的注册人脸图像，构建所述对象群组对应的终端群组的人脸图像集。
  14. 根据权利要求13所述的装置，其中，所述分组部分具体被配置为执行将相同初始 终端群组对应的预设对象，划分到同一对象群组。
  15. 根据权利要求13或14所述的装置，其中，所述分组部分具体被配置为执行将所述多个预设对象中的至少两个目标对象，划分到同一对象群组，所述至少两个目标对象为初始终端群组包括的预设数量个相同支付终端的预设对象。
  16. 根据权利要求13至15任一项所述的装置，其中，所述分析部分具体被配置为执行将所述支付操作信息输入预设支付分析网络进行支付分析，得到所述支付分析结果。
  17. 根据权利要求10至16任一项所述的装置，其中，所述装置还包括：
    第二验证部分，被配置为执行在所述第一身份验证结果指示所述目标人脸图像集未包括与所述待验证人脸图像匹配的目标人脸注册图像的情况下，基于全量人脸图像集，对所述待验证人脸图像进行身份验证，得到第二身份验证结果；
    第二操作执行部分，被配置为执行在所述第二身份验证结果指示所述全量人脸图像集包括所述目标人脸注册图像的情况下，基于所述目标人脸注册图像对应的支付账号执行支付操作。
  18. 根据权利要求10至17任一项所述的装置，其中，所述第一确定部分包括：
    获取单元，被配置为执行获取所述目标支付终端的目标终端标识；
    查询单元，被配置为执行从多个预设终端群组标识中，查询包括所述目标终端标识的目标终端群组标识；
    确定单元，被配置为执行将所述目标终端群组标识对应的终端群组，作为所述目标终端群组。
  19. 一种电子设备，包括：
    处理器；
    用于存储所述处理器可执行指令的存储器；
    其中，所述处理器被配置为执行所述指令，以实现如权利要求1至9中任一项所述的人脸支付方法。
  20. 一种计算机可读存储介质，当所述存储介质中的指令由电子设备的处理器执行时，使得人脸支付设备能够执行如权利要求1至9中任一项所述的人脸支付方法。
  21. 一种计算机程序，包括计算机可读代码，当所述计算机可读代码在电子设备中运行时，所述电子设备中的处理器执行用于实现权利要求1至9任一所述的人脸支付方法。
  22. 一种计算机程序产品，用于存储计算机可读指令，当所述指令被执行时使得计算机执行权利要求1至9任一项所述的人脸支付方法。
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