A method and device for matching a terminal identification mark with a face cluster ID

Abstract

The application provides a terminal identification mark and a face cluster ID matching method and device, the method comprising: obtaining terminal identification marks and face cluster IDs of each target point in a target area; for any target point, determining the time difference between the first time information of any ID terminal identification mark and the second time information of any face cluster ID in the target point; for any target point, determining whether the time difference meets a preset time difference threshold; if yes, determining that the terminal identification mark and the face cluster ID in the target point match successfully; based on a matching success number threshold, determining whether the terminal identification mark and the face cluster ID in the target area match successfully. The application can batch match terminal identification marks and face cluster IDs, and can improve matching efficiency.

Description

Technical Field

[0001] This application relates to the field of identity recognition technology, and in particular to a method and apparatus for matching terminal identification identifiers with face clustering IDs. Background Technology

[0002] With the continuous development of mobile communication technology, mobile terminals are used more and more in people's daily lives, and people's lives are becoming increasingly inseparable from these mobile terminal devices. Moreover, facial recognition technology is being applied more and more widely. In some specific scenarios, if it is necessary to find the identity of a target person in that scenario, the identity of the target person can usually be determined by the target person's terminal identification identifier and facial clustering ID.

[0003] However, in the existing technology, since the target person's terminal may have multiple registered users, it is not possible to directly match the target person's face cluster ID through the target person's terminal identification identifier. Furthermore, in the existing technology, to match the target person's terminal identification identifier with the face cluster ID, it is necessary to rely on the target person's ID card, which is inefficient. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a method and apparatus for matching terminal identification identifiers and face clustering IDs, which can realize batch matching of terminal identification identifiers and face clustering IDs and improve matching efficiency.

[0005] This application provides a method for matching terminal identification identifiers with face clustering IDs, the method comprising:

[0006] Obtain the terminal identification identifier and face clustering ID of each target point in the target area; wherein, the terminal identification identifier carries first time information and first location information, and the face clustering ID carries second time information and second location information;

[0007] For any of the target locations, determine the time difference between the first time information of any of the terminal identification identifiers at the target locations and the second time information of any of the face clustering IDs;

[0008] If the time difference is less than a preset time difference threshold, then it is determined that the terminal identification identifier collected at the target location is successfully matched with the face clustering ID.

[0009] Based on the total number of successful matches between the terminal identification identifier and the face cluster ID at each target location, it is determined whether the terminal identification identifier and the face cluster ID have completed the match.

[0010] Furthermore, after determining the time difference between the first time information of any terminal identification identifier and the second time information of any face clustering ID for any of the target locations, the matching method between the terminal identification identifier and the face clustering ID further includes:

[0011] If the time difference is greater than or equal to a preset time difference threshold, it is determined that the terminal identification identifier collected at the target location does not match the face clustering ID.

[0012] Furthermore, determining whether the terminal identification identifier and the face clustering ID have completed a match based on the total number of successful matches between the terminal identification identifier and the face clustering ID at each target location includes:

[0013] If the total number of successful matches between the terminal identification identifier and the face cluster ID at each target location is greater than or equal to the preset successful match threshold, then the terminal identification identifier and the face cluster ID are considered to have completed the match.

[0014] Furthermore, determining whether the terminal identification identifier and the face clustering ID have successfully matched based on the total number of successful matches between the terminal identification identifier and the face clustering ID at each target location also includes:

[0015] If the total number of successful matches between the terminal identification identifier and the face cluster ID at each target location is less than the preset successful match threshold, then it is determined that the terminal identification identifier and the face cluster ID have not been matched.

[0016] Furthermore, after determining that the terminal identification identifier collected at the target location and the face clustering ID are successfully matched if the time difference is less than a preset time difference threshold, the matching method between the terminal identification identifier and the face clustering ID further includes:

[0017] Record the total number of successful matches between the terminal identification identifier and the face clustering ID at each target location.

[0018] This application embodiment also provides a device for matching terminal identification identifiers with face clustering IDs, the device comprising:

[0019] The acquisition module is used to acquire the terminal identification identifier and face clustering ID of each target point in the target area; wherein, the terminal identification identifier carries first time information and first location information, and the face clustering ID carries second time information and second location information;

[0020] The first determining module is used to determine, for any of the target locations, the time difference between the first time information of any terminal identification identifier and the second time information of any face clustering ID in the target location;

[0021] The second determining module is used to determine that the terminal identification identifier collected at the target location and the face clustering ID are successfully matched if the time difference is less than a preset time difference threshold.

[0022] The third determining module is used to determine whether the terminal identification identifier and the face clustering ID have been successfully matched based on the total number of successful matches between the terminal identification identifier and the face clustering ID at each target location.

[0023] Furthermore, the third determining module is specifically used for:

[0024] If the total number of successful matches between the terminal identification identifier and the face cluster ID at each target location is greater than or equal to the preset successful match threshold, then the terminal identification identifier and the face cluster ID are considered to have completed the match.

[0025] Furthermore, the third determining module is also specifically used for:

[0026] If the total number of successful matches between the terminal identification identifier and the face cluster ID at each target location is less than the preset threshold for successful matches, then it is determined that the identification identifier and the face cluster ID have not been matched.

[0027] This application embodiment also provides an electronic device, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, the steps of the matching method between the terminal identification identifier and the face clustering ID as described above are performed.

[0028] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the method for matching terminal identification identifiers with face clustering IDs as described above.

[0029] Compared with the prior art, the terminal identification identifier and face cluster ID matching method and apparatus provided in this application simultaneously collect terminal identification identifiers and face cluster IDs at various target locations within a target area, determine the time difference between the first time information of any terminal identification identifier and the second time information of any face cluster ID at each target location, and determine whether the terminal identification identifier and face cluster ID at the target location can be successfully matched based on the relationship between the above time difference and a preset time difference threshold. After successful matching, the matching relationship between the terminal identification identifier and face cluster ID within the target area is determined based on a threshold for the number of successful matches. This application can achieve batch matching of terminal identification identifiers and face cluster IDs, which can improve matching efficiency.

[0030] To make the above-mentioned objects, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. 。 Attached Figure Description

[0031] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This document illustrates one of the flowcharts for a matching method between a terminal identification identifier and a face clustering ID provided in an embodiment of this application.

[0033] Figure 2 This illustrates a second flowchart of a matching method between a terminal identification identifier and a face clustering ID provided in an embodiment of this application.

[0034] Figure 3 This diagram illustrates a structural block diagram of a matching device between a terminal identification identifier and a face clustering ID, as provided in an embodiment of this application.

[0035] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of this application is shown.

[0036] In the picture:

[0037] 300 - Device for matching terminal identification identifier with face clustering ID; 310 - Acquisition module; 320 - First determining module; 330 - Second determining module; 340 - Third determining module; 400 - Electronic device; 410 - Processor; 420 - Memory; 430 - Bus 。 Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. Based on the embodiments of this application, every other embodiment obtained by those skilled in the art without inventive effort falls within the scope of protection of this application.

[0039] First, the applicable scenarios for this application will be introduced. This application can be applied to the field of identity recognition technology.

[0040] Research has revealed that, in existing technologies, because a target person's terminal may have multiple registered users, it is impossible to directly match the target person's face cluster ID using the target person's terminal identification identifier. Furthermore, in existing technologies, matching the target person's terminal identification identifier with the face cluster ID requires the assistance of the target person's identification documents, which is inefficient.

[0041] Furthermore, in the existing technology, in the process of determining whether the terminal identification identifier and the face cluster ID can match, it is first necessary to determine the ID card information corresponding to the terminal identification identifier, and then compare the aforementioned ID card information with the face cluster ID to obtain the matching result between the terminal identification identifier and the face cluster ID; or find the target person, directly find the target person's terminal identification identifier and face cluster ID through the target person, and use the target person's facial features to compare the face cluster ID, thereby determining the matching result between the terminal identification identifier and the face cluster ID.

[0042] However, the above matching methods can only be used for a very small number of terminal identification identifiers or face cluster IDs, and cannot quickly and accurately process large amounts of data, which leads to low efficiency. Furthermore, the second matching method mentioned above can only be triggered by one terminal identification identifier or one face cluster ID, and cannot directly mine and determine the matching results between terminal identification identifiers and face cluster IDs across the entire domain.

[0043] Based on this, embodiments of this application provide a base device for a matching method between terminal identification identifiers and face clustering IDs, which can perform batch matching of terminal identification identifiers and face clustering IDs, thereby improving matching efficiency.

[0044] Please see Figure 1 , Figure 1 This is one of the flowcharts illustrating a method for matching a terminal identification identifier with a face clustering ID, as provided in an embodiment of this application. Figure 1 As shown in the illustration, an embodiment of this application provides a method for matching terminal identification identifiers with face clustering IDs, comprising:

[0045] S101. Obtain the terminal identification identifier and face clustering ID of each target point in the target area; wherein, the terminal identification identifier carries first time information and first location information, and the face clustering ID carries second time information and second location information.

[0046] In this step, the target area to be detected is first divided into points, and the terminal identification identifier and face cluster ID under each target point in the target area are determined. Based on the terminal identification identifier and face cluster ID under each target point in the target area, the corresponding terminal identification identifier trajectory and face cluster ID trajectory are generated. It is required that the acquisition direction of the terminal identification identifier and face cluster ID under each target point in the target area is consistent, that is, the perception direction of the acquisition device is consistent.

[0047] Here, the terminal identification identifier can be customized to select different devices for collection according to the needs of different application scenarios. In the embodiments provided in this application, the terminal identification identifier is collected by an electronic fence device under a sensing network.

[0048] The face clustering ID can also be customized to select different devices for collection according to the needs of different application scenarios. In the embodiment provided in this application, the face clustering ID is collected by a face recognition device with face capture function.

[0049] Among them, a sensing network refers to a communication network that can sense the existing network environment, investigate the network configuration in real time through understanding the environment, and intelligently adapt to changes in the professional environment. Furthermore, it possesses the ability to learn from change and apply that learning to future decision-making.

[0050] In this way, the face clustering ID is formed by clustering face capture data, grouping multiple face capture images that may be of the same person together, and assigning a unique ID to each cluster, called the face clustering ID. The face clustering ID is similar to an ID card number, but the difference is that: an ID card number can be matched with a specific person and can be used to retrieve various basic information about that person, while a face clustering ID is just a clustering ID of a group of face capture images, which can only represent multiple faces and cannot find the basic information of multiple corresponding faces.

[0051] S102. For any of the target locations, determine the time difference between the first time information of any of the terminal identification identifiers and the second time information of any of the face clustering IDs at the target locations.

[0052] In this step, the time difference between the first time information of any terminal identification identifier and the second time information of any face clustering ID in the target location can be statistically analyzed and displayed in different ways according to different application scenarios. For example, the statistical and display method of the time difference in the embodiment provided in this application is to display it in the form of a chart.

[0053] Here, the first time information is used to characterize the start time information of the electronic fence device collecting face cluster IDs at the target location, and the second time information is used to characterize the start time information of the face recognition device collecting face cluster IDs at the target location.

[0054] S103. If the time difference is less than a preset time difference threshold, then it is determined that the terminal identification identifier collected at the target location is successfully matched with the face clustering ID.

[0055] In this step, for any target location, the time difference is compared with a preset time difference threshold. Based on the judgment result, it is determined whether the terminal identification identifier and the face cluster ID at that location are successfully matched. If the time difference is less than the preset time difference threshold, it is determined that the terminal identification identifier collected at the target location is successfully matched with the face cluster ID. Furthermore, the total number of successful matches between the terminal identification identifier and the face cluster ID at each target location is recorded.

[0056] Here, the preset time difference threshold is determined in the following way:

[0057] For any of the target locations, cluster the multiple time differences between all first time information of all terminal identification identifiers and all second time information of all face clustering IDs in the target location, and determine the time difference value corresponding to the category with zero time difference after clustering as the preset time difference threshold.

[0058] Here, a specific example illustrates the specific clustering method:

[0059] Suppose that multiple time differences between all first-time information and all second-time information of all face cluster IDs in the target location are clustered using KMEANS (K=10) clustering method, and the time difference value corresponding to the category with zero time difference after clustering is the preset time difference threshold, denoted as [start_add,end_add].

[0060] Here, the total number of successful matches between the terminal identification identifier and the face clustering ID at each target location can be specifically recorded as follows:

[0061] For any of the target locations, determine whether the time difference between the second time information of any two successfully matched terminal identification identifiers and any face cluster ID is less than a preset time interval.

[0062] If so, the number of times the terminal identification identifier and the face clustering ID are successfully mapped at the target location is recorded as one.

[0063] Here, assuming that the preset time interval for any target location is 30 minutes, if the time difference between the second time information of any two successfully matched terminal identification identifiers and any face cluster ID is less than 30 minutes, then the number of times the two terminal identification identifiers are successfully matched is determined to be one.

[0064] If the time difference between the second time information of any two successfully matched terminal identification identifiers and any face cluster ID is greater than 30 minutes, then the number of times the two terminal identification identifiers are successfully matched is determined to be two.

[0065] S104. Based on the total number of successful matches between the terminal identification identifier and the face clustering ID at each target location, determine whether the terminal identification identifier and the face clustering ID have been successfully matched.

[0066] In this step, the system determines whether the terminal identification identifier and the face cluster ID in the target area have been successfully matched based on the threshold for the number of successful matches and the total number of successful matches between the terminal identification identifier and the face cluster ID in each target location within the target area.

[0067] Here, if the terminal identification identifier in the target area matches the face cluster ID, the matching score between the terminal identification identifier and the face cluster ID is determined, and the strength of the matching relationship between the terminal identification identifier and the face cluster ID is determined according to the size of the matching score.

[0068] Compared with the prior art, the method for matching terminal identification identifiers and face cluster IDs provided in this application simultaneously collects terminal identification identifiers and face cluster IDs at various target locations within a target area, determines the time difference between the first time information of any terminal identification identifier and the second time information of any face cluster ID at each target location, and judges whether the terminal identification identifier and face cluster ID at the target location can be successfully matched based on the relationship between the above time difference and a preset time difference threshold. After successful matching, the matching relationship between terminal identification identifiers and face cluster IDs within the target area is determined based on a threshold for the number of successful matches. This application can achieve batch matching of terminal identification identifiers and face cluster IDs, which can improve matching efficiency.

[0069] Please see Figure 2 , Figure 2 This is a second flowchart illustrating a method for matching terminal identification identifiers with face clustering IDs, provided as an embodiment of this application. Figure 2 As shown in the embodiments of this application, the matching method between terminal identification identifiers and face clustering IDs includes:

[0070] S201. Obtain the terminal identification identifier and face clustering ID of each target point in the target area; wherein, the terminal identification identifier carries first time information and first location information, and the face clustering ID carries second time information and second location information.

[0071] S202. For any of the target locations, determine the time difference between the first time information of any of the terminal identification identifiers and the second time information of any of the face clustering IDs at the target locations.

[0072] S203. If the time difference is less than a preset time difference threshold, then it is determined that the terminal identification identifier collected at the target location is successfully matched with the face clustering ID.

[0073] S204. If the total number of successful matches between the terminal identification identifier and the face cluster ID at each target location is greater than or equal to the preset successful match threshold, then the terminal identification identifier and the face cluster ID are determined to have completed the match.

[0074] In this step, assuming the threshold for successful matching is 10 times, after determining that the number of successful matchings between the terminal identification identifier and the face cluster ID at each target location in the target area is greater than or equal to the threshold of 10 successful matchings, it is determined that the terminal identification identifier and the face cluster ID in the target area are successfully matched, and the matching score between the terminal identification identifier and the face cluster ID in the target area is calculated.

[0075] Here, the expression for matching the score can be specifically as follows:

[0076] score=log(min(#map,100)) / 10;

[0077] Among them, "#map" is used to represent the number of times the terminal identification identifier and the face clustering ID are successfully matched.

[0078] S205. If the total number of successful matches between the terminal identification identifier and the face cluster ID at each target location is less than the preset successful match threshold, then the terminal identification identifier and the face cluster ID are determined to have not been matched.

[0079] In this step, after determining that the number of successful matches between the terminal identification identifier and the face clustering ID at each target location in the target area is less than the threshold of 10 successful matches, it is determined that the terminal identification identifier and the face clustering ID in the target area have not been successfully matched.

[0080] The descriptions of S201 to S204 can be referred to those of S101 to S104, and the same technical effect can be achieved, so they will not be elaborated further.

[0081] Compared with the prior art, the method for matching terminal identification identifiers and face cluster IDs provided in this application simultaneously collects terminal identification identifiers and face cluster IDs at various target locations within a target area, determines the time difference between the first time information of any terminal identification identifier and the second time information of any face cluster ID at each target location, and judges whether the terminal identification identifier and face cluster ID at the target location can be successfully matched based on the relationship between the above time difference and a preset time difference threshold. After successful matching, the matching relationship between terminal identification identifiers and face cluster IDs within the target area is determined based on a threshold for the number of successful matches. This application can achieve batch matching of terminal identification identifiers and face cluster IDs, which can improve matching efficiency.

[0082] Please see Figure 3 , Figure 3 This is a structural block diagram of a device for matching terminal identification identifiers with face clustering IDs, provided in an embodiment of this application. Figure 3 As shown, the terminal identification identifier and face clustering ID matching device 300 includes:

[0083] The acquisition module 310 is used to acquire the terminal identification identifier and face clustering ID of each target point in the target area; wherein the terminal identification identifier carries first time information and first location information, and the face clustering ID carries second time information and second location information.

[0084] The first determining module 320 is used to determine, for any of the target locations, the time difference between the first time information of any terminal identification identifier and the second time information of any face clustering ID.

[0085] The second determining module 330 is used to determine that the terminal identification identifier collected at the target location and the face clustering ID are successfully matched if the time difference is less than a preset time difference threshold.

[0086] Furthermore, after determining the time difference between the first time information of any terminal identification identifier and the second time information of any face clustering ID for any of the target locations, the matching method between the terminal identification identifier and the face clustering ID further includes:

[0087] If the time difference is greater than or equal to a preset time difference threshold, it is determined that the terminal identification identifier collected at the target location does not match the face clustering ID.

[0088] The third determining module 340 is used to determine whether the terminal identification identifier and the face clustering ID have been successfully matched based on the total number of successful matches between the terminal identification identifier and the face clustering ID at each target location.

[0089] Furthermore, the preset time difference threshold is determined in the following way:

[0090] Furthermore, the third determining module 340 is specifically used for:

[0091] If the total number of successful matches between the terminal identification identifier and the face cluster ID at each target location is greater than or equal to the preset successful match threshold, then the terminal identification identifier and the face cluster ID are considered to have completed the match.

[0092] Furthermore, the third determining module 340 is specifically used for:

[0093] If the total number of successful matches between the terminal identification identifier and the face cluster ID at each target location is less than the preset successful match threshold, then it is determined that the terminal identification identifier and the face cluster ID have not been matched.

[0094] Furthermore, after determining that the terminal identification identifier collected at the target location and the face clustering ID are successfully matched if the time difference is less than a preset time difference threshold, the matching method between the terminal identification identifier and the face clustering ID further includes:

[0095] Record the total number of successful matches between the terminal identification identifier and the face clustering ID at each target location.

[0096] Compared with the prior art, the terminal identification identifier and face cluster ID matching device provided in this application embodiment simultaneously collects terminal identification identifiers and face cluster IDs at various target locations within a target area, determines the time difference between the first time information of any terminal identification identifier and the second time information of any face cluster ID at each target location, and judges whether the terminal identification identifier and face cluster ID at the target location can be successfully matched based on the relationship between the above time difference and a preset time difference threshold. After successful matching, the matching relationship between the terminal identification identifier and face cluster ID within the target area is determined based on the number of successful matching times threshold. This application can realize batch matching of terminal identification identifiers and face cluster IDs, which can improve matching efficiency.

[0097] Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 4 As shown, the electronic device 400 includes a processor 410, a memory 420, and a bus 430.

[0098] The memory 420 stores machine-readable instructions executable by the processor 410. When the electronic device 400 is running, the processor 410 communicates with the memory 420 via the bus 430. When the machine-readable instructions are executed by the processor 410, they can perform the operations described above. Figure 1 as well as Figure 2 The steps of the matching method between the terminal identification identifier and the face clustering ID in the method embodiment shown are described in detail in the method embodiment, and will not be repeated here.

[0099] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, can perform the above-described actions. Figure 1 as well as Figure 2 The steps of the matching method between the terminal identification identifier and the face clustering ID in the method embodiment shown are described in detail in the method embodiment, and will not be repeated here.

[0100] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0101] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the shown or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0102] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0103] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0104] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0105] Finally, it should be noted that the above-described embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The protection scope of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this application. Such modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be determined by the protection scope of the claims. 。

Claims

1. A method for matching between a terminal identification and a face cluster ID, the method comprising: receiving a face image from a terminal; extracting a face feature from the face image; and matching the face feature with a face cluster ID. The terminal identification and the face cluster ID matching method comprises the following steps: Obtain the terminal identification and the face cluster ID of each target point in a target area, wherein the terminal identification carries first time information and first position information, the face cluster ID carries second time information and second position information, and the terminal identification and the face cluster ID of each target point in the target area are collected in the same direction; For any target point, determine the time difference between the first time information of any terminal identification and the second time information of any face cluster ID; If the time difference is less than a preset time difference threshold, it is determined that the terminal identification and the face cluster ID collected at the target point are matched successfully; Determine whether the terminal identification and the face cluster ID are matched based on the total number of successful matches of the terminal identification and the face cluster ID at each target point; The preset time difference threshold is determined by the following method: For any target point, cluster the multiple time differences between the first time information of all terminal identifications and the second time information of all face cluster IDs, and determine the time difference value corresponding to the class with a clustered time difference of zero as the preset time difference threshold. 2.The method of claim 1, wherein, After determining the time difference between the first time information of any terminal identification and the second time information of any face cluster ID for any target point, the terminal identification and the face cluster ID matching method further comprises the following steps: If the time difference is greater than or equal to the preset time difference threshold, it is determined that the terminal identification and the face cluster ID collected at the target point are not matched successfully. 3.The method of claim 1, wherein, The determination of whether the terminal identification and the face cluster ID are matched based on the total number of successful matches of the terminal identification and the face cluster ID at each target point comprises the following steps: If it is determined that the total number of successful matches of the terminal identification and the face cluster ID at each target point is greater than or equal to a preset number of successful match threshold, it is determined that the terminal identification and the face cluster ID are matched. 4.The method of claim 1, wherein, The determination of whether the terminal identification and the face cluster ID are matched based on the total number of successful matches of the terminal identification and the face cluster ID at each target point further comprises the following steps: If it is determined that the total number of successful matches of the terminal identification and the face cluster ID at each target point is less than the preset number of successful match threshold, it is determined that the terminal identification and the face cluster ID are not matched. 5.The method of claim 1, wherein, After it is determined that the terminal identification and the face cluster ID collected at the target point are matched successfully if the time difference is less than the preset time difference threshold, the terminal identification and the face cluster ID matching method further comprises the following steps: Record the total number of successful matches of the terminal identification and the face cluster ID at each target point.

6. A matching device between a terminal identification identifier and a face clustering ID, characterized in that, The terminal identification and the face cluster ID matching device comprises the following steps: The acquisition module is configured to acquire terminal identification marks and face cluster IDs of each target point in a target area, wherein the terminal identification mark carries first time information and first position information, and the face cluster ID carries second time information and second position information; the terminal identification mark and the face cluster ID of each target point in the target area are collected in the same direction; The first determination module is configured to determine, for any target point, a time difference between the first time information of any terminal identification mark and the second time information of any face cluster ID of the target point; The second determination module is configured to determine that the terminal identification mark and the face cluster ID collected at the target point are successfully matched if the time difference is less than a preset time difference threshold; The third determination module is configured to determine whether the terminal identification mark and the face cluster ID are matched based on a total number of successful matches of the terminal identification mark and the face cluster ID at each target point; The first determination module is further configured to determine the preset time difference threshold by the following method: For any target point, a plurality of time differences between all first time information of all terminal identification marks and all second time information of all face cluster IDs of the target point are clustered, and a time difference value corresponding to a class with a clustered time difference of zero is determined as the preset time difference threshold.

7. The terminal of claim 6, wherein the matching between the identification and the face cluster ID is performed by a matching algorithm. The third determination module is specifically configured to: If it is determined that the total number of successful matches of the terminal identification mark and the face cluster ID at each target point is greater than or equal to a preset match success threshold, it is determined that the terminal identification mark and the face cluster ID are matched. 8.The terminal of claim 6, wherein the terminal identifies a match between the terminal identification and the face cluster ID. The third determination module is further specifically configured to: If it is determined that the total number of successful matches of the terminal identification mark and the face cluster ID at each target point is less than the preset match success threshold, it is determined that the terminal identification mark and the face cluster ID are not matched.

9. An electronic device, comprising: The processor, the memory and the bus, the memory stores the machine readable instructions executable by the processor, when the electronic device runs, the processor and the memory are communicated through the bus, the machine readable instructions are executed by the processor to execute the steps of the terminal identification mark and the face cluster ID matching method in any one of claims 1-5. The computer readable storage medium stores a computer program, and the computer program is executed by the processor to execute the steps of the terminal identification mark and the face cluster ID matching method in any one of claims 1-5.

10. A computer-readable storage medium, characterized in that, ​

Images