Information update method and device, storage medium, and electronic device

Abstract

An embodiment of the present invention provides an information update method, an apparatus, a storage medium, and an electronic device. The method includes: obtaining first fingerprint information of a target object acting on a target device and first face information within a preset distance of the target device; when the first face information matches the target face information of the target object, obtaining target fingerprint information, where the target fingerprint information is associated with the target object and is used to verify the first fingerprint information; and updating the target fingerprint information using the first fingerprint information. Through the present invention, the problem of low fingerprint recognition accuracy in the related art is solved, and the effect of increasing the fingerprint recognition accuracy is achieved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of communications, and in particular, to a method and apparatus for information update, a storage medium, and an electronic device. Background Art

[0002] As a kind of biometric recognition, fingerprint recognition has gradually become a popular technology after years of development and is widely used in life. For example, capacitive screen fingerprint recognition on mobile phones applies 1:1 fingerprint comparison, and other authentication fields such as password locks, password boxes, access control security, etc. In terms of use, on the one hand, the user extracts fingerprint features from the input fingerprint image, and on the other hand, when the user uses it, the immediate fingerprint is collected by pressing. After the feature value is extracted through the fingerprint algorithm model, it is compared with the existing fingerprint. The two common scenarios are 1:N and 1:1 comparison. In order to improve the accuracy of fingerprint recognition, the commonly used method in the prior art is to increase the number of fingerprint collections when inputting fingerprints. However, this method still has the problems of irrational collected fingerprint information and inaccurate subsequent fingerprint recognition. Summary of the Invention

[0003] The embodiments of the present invention provide a method and apparatus for information update, a storage medium, and an electronic device, so as to at least solve the problem of low fingerprint recognition accuracy in the related art.

[0004] According to an embodiment of the present invention, there is provided an information update method, including: obtaining first fingerprint information of a target object acting on a target device and first face information within a preset distance of the target device; obtaining target fingerprint information when the first face information matches the target face information of the target object, where the target fingerprint information is associated with the target object and is used to verify the first fingerprint information; and updating the target fingerprint information by using the first fingerprint information.

[0005] According to another embodiment of the present invention, there is provided an information update apparatus, including: a first obtaining module, configured to obtain first fingerprint information of a target object acting on a target device and first face information within a preset distance of the target device; a second obtaining module, configured to obtain target fingerprint information when the first face information matches the target face information of the target object, where the target fingerprint information is associated with the target object and is used to verify the first fingerprint information; and a first update module, configured to update the target fingerprint information by using the first fingerprint information.

[0006] In an exemplary embodiment, the above-mentioned first acquisition module includes: a first acquisition unit, configured to acquire N frames of images of the object when the object is included within the preset distance, where N is a natural number greater than or equal to 1; a first determination unit, configured to determine a target image from the N frames of images when it is determined that the first fingerprint information acts on the target device; a first extraction unit, configured to extract the first face information from the target image; a second acquisition unit, configured to acquire the first fingerprint information of the target object acting on the target device through a fingerprint sensing device in the target device.

[0007] In an exemplary embodiment, the above-mentioned first acquisition module includes: a third acquisition unit, configured to acquire the first fingerprint information of the target object acting on the target device through a fingerprint sensing device in the target device; a fourth acquisition unit, configured to acquire N frames of images of an object within a preset distance of the target device when it is determined that the first fingerprint information does not act on the target device, where N is a natural number greater than or equal to 1; a second extraction unit, configured to extract the first face information from the target image.

[0008] In an exemplary embodiment, the above-mentioned device further includes: a first comparison module, configured to compare the first face information with the target face information of the target object before acquiring the target fingerprint information when the first face information matches the target face information of the target object; a first replacement module, configured to replace the association relationship between the target face information and the target object with the association relationship between the first face information and the target object when the first face information matches the target face information and the face features of the first face information are superior to the face features of the target face information; a first association module, configured to associate the first face information with the target object when the first face information and the target face information do not match.

[0009] In an exemplary embodiment, the above-mentioned device further includes: a third acquisition module, configured to acquire M pieces of face information associated with the target object from a database, where M is a natural number greater than 1; a second determination module, configured to determine the face information with the largest face feature value among the M pieces of face information as the target face information, where the target face information is used to identify the target object.

[0010] In an exemplary embodiment, the above-mentioned first update module includes: a first update unit, configured to update the target fingerprint information with the first fingerprint information when the first fingerprint information corresponds to the target object.

[0011] In an exemplary embodiment, the first update unit includes: a first update subunit configured to update the points in the target fingerprint information according to the points in the first fingerprint information.

[0012] In an exemplary embodiment, the apparatus further includes: a fourth acquisition module configured to acquire P fingerprint information of the target object acting on the target device before acquiring the first fingerprint information of the target object acting on the target device and the first face information within a preset distance of the target device, where P is a natural number greater than 1; a third determination module configured to determine K key points of the fingerprint of the target object from the P fingerprint information, where K is a natural number greater than 1; a fourth determination module configured to determine the target fingerprint information based on the K key points.

[0013] According to another embodiment of the present invention, there is also provided a computer-readable storage medium storing a computer program, where the computer program is configured to execute the steps in any of the above method embodiments when running.

[0014] According to another embodiment of the present invention, there is also provided an electronic device including a memory and a processor, where the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any of the above method embodiments.

[0015] Through the present invention, by acquiring the first fingerprint information of the target object acting on the target device and the first face information within a preset distance of the target device; and acquiring the target fingerprint information when the first face information matches the target face information of the target object, where the target fingerprint information is associated with the target object and is used to verify the first fingerprint information; and updating the target fingerprint information using the first fingerprint information. The purpose of optimizing the fingerprint verification of the object in combination with the face information is achieved. Therefore, the problem of low fingerprint recognition accuracy in the related art can be solved, and the effect of increasing the fingerprint recognition accuracy can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a hardware structure block diagram of a mobile terminal of an information update method according to an embodiment of the present invention;

[0017] Figure 2 is a flowchart of an information update method according to an embodiment of the present invention;

[0018] Figure 3 is a flowchart of fingerprint acquisition according to an embodiment of the present invention;

[0019] Figure 4 is a fingerprint verification flowchart according to an embodiment of the present invention;

[0020] Figure 5 It is a structural block diagram of an information update device according to an embodiment of the present invention. Detailed implementation manners

[0021] In the following, embodiments of the present invention will be described in detail with reference to the accompanying drawings and in conjunction with the embodiments.

[0022] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence.

[0023] The method embodiments provided in the embodiments of the present application can be executed on a mobile terminal, a computer terminal, or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 It is a hardware structural block diagram of a mobile terminal of an information update method according to an embodiment of the present invention. As Figure 1 shown, the mobile terminal may include one or more ( Figure 1 only one is shown in Figure 1 the processor 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Among them, the above-mentioned mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those of ordinary skill in the art can understand that Figure 1 the structure shown in Figure 1 is only schematic and does not limit the structure of the above-mentioned mobile terminal. For example, the mobile terminal may further include more or fewer components than

[0024] shown in

[0025] The transmission device 106 is used to receive or send data via a network. Specific examples of the above-mentioned network may include a wireless network provided by a communication provider of a mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, abbreviated as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a Radio Frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0026] In this embodiment, an information update method is provided. Figure 2 It is a flowchart of the information update method according to an embodiment of the present invention, as Figure 2 shown, and the process includes the following steps:

[0027] Step S202, obtain the first fingerprint information of the target object acting on the target device and the first face information within a preset distance of the target device;

[0028] In this embodiment, the target device includes a fingerprint recognition device and a camera device. For example, an access control lock. The preset distance can be the distance when the user approaches the target device.

[0029] Step S204, when the first face information matches the target face information of the target object, obtain the target fingerprint information, where the target fingerprint information is associated with the target object, and the target fingerprint information is used to verify the first fingerprint information;

[0030] In this embodiment, the first face information can be associated with the target object whether it is the face information of the target object or not. Only when the first face information matches the target face information of the target object can the target fingerprint information be obtained.

[0031] Step S206, update the target fingerprint information using the first fingerprint information.

[0032] In this embodiment, the association between the face information and the target object does not involve authentication and does not affect the processing efficiency of fingerprints. It only serves as a graphical representation of the fingerprint pressing object and is used to determine the ownership of the fingerprint. It can play a role in subsequent positioning of whether the same person swipes the fingerprint. For example, in the scenario of unit attendance, if there is employee face gallery information, the situation of proxy punching and the information of the person who punches the card on behalf of others can be retrieved according to the face features in the statistical distribution.

[0033] Among them, the execution subject of the above steps can be a terminal, etc., but is not limited thereto.

[0034] Through the above steps, by obtaining the first fingerprint information of the target object acting on the target device and the first face information within a preset distance of the target device; when the first face information matches the target face information of the target object, obtaining target fingerprint information, where the target fingerprint information is associated with the target object and is used to verify the first fingerprint information; and updating the target fingerprint information with the first fingerprint information. The purpose of optimizing the fingerprint verification of the object in combination with the face information is achieved. Therefore, the problem of low fingerprint recognition accuracy in the related art can be solved, and the effect of increasing the fingerprint recognition accuracy can be achieved.

[0035] In an exemplary embodiment, obtaining the first fingerprint information of the target object acting on the target device and the first face information within a preset distance of the target device includes:

[0036] S11, when there is an object within the preset distance, obtaining N frames of images of the object, where N is a natural number greater than or equal to 1;

[0037] S12, when it is determined that the first fingerprint information acts on the target device, determining the target image from the N frames of images;

[0038] S13, extracting the first face information from the target image, where the target image is included in the N frames of images;

[0039] S14, obtaining the first fingerprint information of the target object acting on the target device through the fingerprint sensing device in the target device.

[0040] In this embodiment, the object image is obtained first, and then the fingerprint information is obtained.

[0041] In an exemplary embodiment, obtaining the first fingerprint information of the target object acting on the target device and the first face information within a preset distance of the target device includes:

[0042] S21, obtaining the first fingerprint information of the target object acting on the target device through the fingerprint sensing device in the target device;

[0043] S22, when it is determined that the first fingerprint information does not act on the target device, obtaining N frames of images of the object within the preset distance of the target device, where N is a natural number greater than or equal to 1;

[0044] S23, extracting the first face information from the target image, where the target image is included in the N frames of images.

[0045] In this embodiment, the fingerprint information is obtained first, and then the object image is obtained.

[0046] The above methods for obtaining fingerprint information and face images include the following embodiments: When the user approaches the access control lock, the video capture sensor (sensor) set in the access control lock is used to continuously capture the user's video stream. When the user presses the fingerprint, before and after this process, the face feature value is extracted from the face image that is the most frontal from the user's perspective and has the best recognition effect, and the face feature value is associated with the fingerprint user.

[0047] In an exemplary embodiment, before obtaining the target fingerprint information when the first face information matches the target face information of the target object, the method further includes:

[0048] S31. Compare the first face information with the target face information;

[0049] S32. When the first face information matches the target face information and the face features of the first face information are superior to those of the target face information, replace the association relationship between the target face information and the target object with the association relationship between the first face information and the target object;

[0050] S33. When the first face information and the target face information do not match, associate the first face information with the target object.

[0051] In this embodiment, for example, during the continuous use of fingerprint recognition, the captured face information is compared with the stored face information. When the face feature values match, the one with more acquisition points among the two face feature values is saved; when the face feature values do not match, the face feature value of the first face information obtained is retained, and the number of face features associated with the fingerprint information increases by one. When used multiple times, the distribution of the portrait feature values of the person who operates frequently will become prominent (i.e., the relationship graph is determined), so that it is possible to confirm which feature value the fingerprint belongs to from the statistical data.

[0052] In an exemplary embodiment, the method further includes:

[0053] S41. Obtain M face information associated with the target object from the database, where M is a natural number greater than 1;

[0054] S42. Determine the face information with the largest face feature value among the M face information as the target face information, where the target face information is used to identify the target object.

[0055] In this embodiment, the target object can be associated with multiple face information to form graph information.

[0056] In an exemplary embodiment, updating the target fingerprint information using the first fingerprint information includes:

[0057] S51. When the first fingerprint information corresponds to the target object, update the target fingerprint information using the first fingerprint information.

[0058] Among them, updating the target fingerprint information using the first fingerprint information includes: updating the points in the target fingerprint information according to the points in the first fingerprint information.

[0059] In this embodiment, for example, after a certain user is determined, the fingerprint of this user is collected. When the weight exceeds a certain threshold, compare the first fingerprint information with the retained second fingerprint information, update the values of the corresponding points, generate a new fingerprint template, and use the generated new fingerprint template as the latest fingerprint template to wait for the next verification. In this way, during multiple collection processes, new points are added, and old points are updated based on better comparison. Eventually, the fingerprint of this user gets closer and closer to the actual situation during the self-learning process, achieving the purpose of enhancing the recognition accuracy.

[0060] In an exemplary embodiment, before obtaining the first fingerprint information of the target object acting on the target device and the first face information within the preset distance of the target device, the method further includes:

[0061] S61. Obtain M fingerprint information of the target object acting on the target device, where M is a natural number greater than 1;

[0062] S62. Determine K key points of the fingerprint of the target object from the M fingerprint information, where K is a natural number greater than 1;

[0063] S63. Determine the target fingerprint information of the target object based on the K key points, where the target fingerprint information is used to verify the first fingerprint information.

[0064] In this embodiment, as Figure 3 shown, it is the process of fingerprint collection. When fingerprint is being entered, the user needs to input 3 - 5 times until it is determined that the necessary number of feature points is collected, and then the user will be informed that the collection is completed. During this process, through the fusion of 3 - 5 fingerprint templates, the parts with relatively obvious retained features at each point are retained.

[0065] The following describes the present application with specific embodiments:

[0066] This embodiment automatically determines the fingerprint attribution using the statistical distribution of face features, and performs a self-learning template fusion optimization strategy for fingerprints according to the attribution. It improves continuous optimization during actual use, enhances fingerprint recognition accuracy, and reduces the false rejection rate and false recognition rate. As Figure 4 shown, this embodiment includes the following steps:

[0067] S401. The fingerprint recognition module adds a video capture sensor. Starting when the user approaches, it continuously captures a portrait video stream. When the user presses the fingerprint, it extracts the feature values of the face image with the most upright user angle and the best recognition effect before and after this process, and associates the face feature values with the fingerprint user. In this process, it does not seek to enforce a strong match between the user feature values and the fingerprint, but only as a statistical means.

[0068] S402. After the fingerprint is continuously used, the face feature values captured by the user are compared with the existing face feature values. When the face feature values can match, it saves the one with more collection points and better quality among the two face feature values, and the statistical count increments by one. When the face feature values do not match, it retains the face feature values, and the number of fingerprint-associated portrait features increases by one. When used multiple times, the distribution of the portrait feature values of the person who operates frequently will become prominent, so that it can be confirmed which face feature values the fingerprint belongs to from the statistical data.

[0069] S403. When a certain person is determined, for each collection of the fingerprint of this object, when the weight exceeds a certain threshold, it compares the fingerprint with the retained fingerprint feature values, updates the values of the corresponding points, generates a new fingerprint template, and uses the generated new fingerprint template as the latest fingerprint template to wait for the next verification. In this way, during multiple collection processes, it adds new points and updates the old points based on a better comparison. Eventually, the fingerprint of this user will get closer and closer to the actual situation during the self-learning process, achieving the purpose of enhancing the recognition accuracy.

[0070] In summary, the face image and portrait obtained in this embodiment do not involve the authentication of fingerprint information, do not affect the processing efficiency of fingerprint recognition, and only serve as a graphical representation of the fingerprint pressing object. It can indirectly determine the ownership of the corresponding fingerprint in big data analysis and can play a role in subsequent identification of whether the same person swipes the fingerprint. The user fingerprint map constructed in this embodiment can enhance the fingerprint recognition accuracy.

[0071] Through the description of the above implementation manners, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disc), including several instructions to enable a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present invention.

[0072] In this embodiment, an information update device is further provided. This device is used to implement the above-mentioned embodiments and preferred implementation manners, and those that have been described will not be elaborated again. As used hereinafter, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0073] Figure 5 is a structural block diagram of an information update device according to an embodiment of the present invention. As Figure 5 shown, the device includes:

[0074] A first acquisition module 52, which acquires the first fingerprint information of the target object acting on the target device and the first face information within a preset distance of the target device;

[0075] A second acquisition module 54, which is used to acquire target fingerprint information when the first face information matches the target face information of the target object, wherein the target fingerprint information is associated with the target object, and the target fingerprint information is used to verify the first fingerprint information;

[0076] A first update module 56, which is used to update the target fingerprint information by using the first fingerprint information.

[0077] In an exemplary embodiment, the first acquisition module includes:

[0078] A first acquisition unit, which is used to acquire N frames of images of the object when the object is included within the preset distance, where N is a natural number greater than or equal to 1;

[0079] A first determination unit, which is used to determine a target image from the N frames of images when it is determined that the first fingerprint information acts on the target device;

[0080] A first extraction unit, which is used to extract the first face information from the target image;

[0081] A second acquisition unit, which is used to acquire the first fingerprint information of the target object acting on the target device through a fingerprint sensing device in the target device.

[0082] In an exemplary embodiment, the first acquisition module includes:

[0083] A third acquisition unit, which is used to acquire the first fingerprint information of the target object acting on the target device through a fingerprint sensing device in the target device;

[0084] A fourth acquisition unit, configured to acquire N frames of images of an object within a preset distance of the target device when it is determined that the above-mentioned first fingerprint information is not applied to the target device, where N is a natural number greater than or equal to 1;

[0085] A second extraction unit, configured to extract the above-mentioned first face information from the target image, where the target image is included in the N frames of images.

[0086] In an exemplary embodiment, the above-mentioned apparatus further includes:

[0087] A first comparison module, configured to compare the above-mentioned first face information with the target face information of the target object before acquiring the target fingerprint information when the above-mentioned first face information matches the target face information of the target object;

[0088] A first replacement module, configured to replace the association relationship between the above-mentioned target face information and the target object with the association relationship between the above-mentioned first face information and the target object when the above-mentioned first face information matches the target face information of the target object and the face features of the above-mentioned first face information are superior to the face features of the target face information of the target object;

[0089] A first association module, configured to associate the above-mentioned first face information with the target object when the above-mentioned first face information and the target face information do not match.

[0090] In an exemplary embodiment, the above-mentioned apparatus further includes:

[0091] A third acquisition module, configured to acquire M pieces of face information associated with the target object from a database, where M is a natural number greater than 1;

[0092] A second determination module, configured to determine the face information with the largest face feature value among the above-mentioned M pieces of face information as the above-mentioned target face information, where the above-mentioned target face information is used to identify the target object.

[0093] In an exemplary embodiment, the above-mentioned first update module includes:

[0094] A first update unit, configured to update the above-mentioned target fingerprint information by using the above-mentioned first fingerprint information when the above-mentioned first fingerprint information corresponds to the target object.

[0095] In an exemplary embodiment, the above-mentioned first update unit includes:

[0096] A first update subunit, configured to update the points in the above-mentioned target fingerprint information according to the points in the above-mentioned first fingerprint information.

[0097] In an exemplary embodiment, the above-mentioned device further includes:

[0098] A fourth acquisition module, configured to acquire P fingerprint information of the target object acting on the target device before acquiring the first fingerprint information of the target object acting on the target device and the first face information within a preset distance of the target device, where P is a natural number greater than 1;

[0099] A third determination module, configured to determine K key points of the fingerprint of the target object from the P fingerprint information, where K is a natural number greater than 1;

[0100] A fourth determination module, configured to determine the target fingerprint information based on the K key points.

[0101] It should be noted that the above-mentioned modules can be implemented by software or hardware. For the latter, it can be implemented in the following ways, but not limited to: all the above-mentioned modules are located in the same processor; or, the above-mentioned modules are respectively located in different processors in any combination form.

[0102] An embodiment of the present invention further provides a computer-readable storage medium, in which a computer program is stored, and the computer program is configured to execute the steps in any one of the above-mentioned method embodiments when running.

[0103] In this embodiment, the above-mentioned computer-readable storage medium can be configured to store a computer program for executing the above steps.

[0104] In an exemplary embodiment, the above-mentioned computer-readable storage medium may include, but is not limited to: USB flash drives, read-only memories (ROM for short), random access memories (RAM for short), mobile hard disks, magnetic disks, or optical discs and other various media that can store computer programs.

[0105] An embodiment of the present invention further provides an electronic device, including a memory and a processor, where a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above-mentioned method embodiments.

[0106] In an exemplary embodiment, the above-mentioned electronic device may further include a transmission device and an input / output device, where the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0107] In an exemplary embodiment, the above-mentioned processor may be configured to execute the above steps through a computer program.

[0108] For the specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary embodiments, and details thereof will not be elaborated herein.

[0109] Obviously, those skilled in the art should understand that the various modules or steps of the present invention described above can be implemented by a general-purpose computing device. They can be concentrated on a single computing device or distributed over a network composed of multiple computing devices. They can be implemented by program codes executable by the computing device. Thus, they can be stored in a storage device and executed by the computing device. And in some cases, the steps shown or described can be executed in a sequence different from that here, or they can be separately fabricated into individual integrated circuit modules, or multiple modules or steps among them can be fabricated into a single integrated circuit module for implementation. In this way, the present invention is not limited to any specific combination of hardware and software.

[0110] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An information update method, characterized in that, Including: Obtaining first fingerprint information of a target object acting on a target device and first face information within a preset distance of the target device; When the first face information matches the target face information of the target object, obtaining target fingerprint information, where the target fingerprint information is associated with the target object and is used to verify the first fingerprint information; Updating the target fingerprint information using the first fingerprint information; Wherein, before obtaining the target fingerprint information when the first face information matches the target face information of the target object, the method further includes: comparing the first face information with the target face information; when the first face information matches the target face information and the face features of the first face information are superior to those of the target face information, replacing the association relationship between the target face information and the target object with the association relationship between the first face information and the target object; when the first face information and the target face information do not match, associating the first face information with the target object, where the situation that the face features of the first face information are superior to those of the target face information includes: the acquisition points in the face feature values of the first face information are superior to the acquisition points in the face features of the target face information.

2. The method according to claim 1, wherein Obtaining first fingerprint information of a target object acting on a target device and first face information within a preset distance of the target device includes: When there is an object within the preset distance, obtaining N frame images of the object, where N is a natural number greater than or equal to 1; When it is determined that the first fingerprint information acts on the target device, determining a target image from the N frame images; Extracting the first face information from the target image; Obtaining the first fingerprint information of the target object acting on the target device through a fingerprint sensing device in the target device.

3. The method according to claim 1, wherein Obtaining first fingerprint information of a target object acting on a target device and first face information within a preset distance of the target device includes: Obtaining the first fingerprint information of the target object acting on the target device through a fingerprint sensing device in the target device; When it is determined that the first fingerprint information does not act on the target device, obtaining N frame images of an object within a preset distance of the target device, where N is a natural number greater than or equal to 1; Extracting the first face information from a target image, where the target image is included in the N frame images.

4. The method according to claim 1, characterized in that, The method further includes: Obtaining M face information associated with the target object from a database, where M is a natural number greater than 1; Determining the face information with the largest face feature value among the M face information as the target face information, where the target face information is used to identify the target object.

5. The method according to claim 1, wherein Updating the target fingerprint information using the first fingerprint information includes: When the first fingerprint information corresponds to the target object, update the target fingerprint information using the first fingerprint information.

6. The method according to claim 5, wherein Updating the target fingerprint information using the first fingerprint information includes: Updating the points in the target fingerprint information according to the points in the first fingerprint information.

7. The method according to claim 1, wherein Before obtaining the first fingerprint information of the target object acting on the target device and the first face information within the preset distance of the target device, the method further includes: Obtaining P fingerprint information of the target object acting on the target device, where P is a natural number greater than 1; Determining K key points of the fingerprint of the target object from the P fingerprint information, where K is a natural number greater than 1; Determining the target fingerprint information from the K key points.

8. An information updating device, characterized in that, including: A first acquisition module that acquires the first fingerprint information of the target object acting on the target device and the first face information within the preset distance of the target device; A second acquisition module, configured to acquire target fingerprint information when the first face information matches the target face information of the target object, where the target fingerprint information is associated with the target object, and the target fingerprint information is used to verify the first fingerprint information; A first update module, configured to update the target fingerprint information using the first fingerprint information; Among them, the second acquisition module is further configured to compare the first face information with the target face information; when the first face information matches the target face information and the face features of the first face information are superior to the face features of the target face information, replace the association relationship between the target face information and the target object with the association relationship between the first face information and the target object; when the first face information and the target face information do not match, associate the first face information with the target object, where the situation that the face features of the first face information are superior to the face features of the target face information includes: the acquisition points in the face feature values of the first face information are superior to the acquisition points in the face features of the target face information.

9. A computer-readable storage medium, characterized in that, A computer program is stored in the computer-readable storage medium, where the computer program, when executed by a processor, implements the method described in any one of claims 1 to 7.

10. An electronic device, comprising a memory and a processor, characterized in that, A computer program is stored in the memory, and the processor is set to run the computer program to execute the method described in any one of claims 1 to 7.

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