Identity recognition methods and devices, electronic devices, storage media

Abstract

This application discloses an identity recognition method, apparatus, electronic device, and storage medium. The method includes: acquiring historical device parameters corresponding to a target object to be identified, wherein the historical device parameters are device parameters used to collect identity recognition information during the historical identity recognition process of the target object; then, adjusting the device parameters of the current acquisition device according to the historical device parameters, so as to collect the identity recognition information of the target object through the current acquisition device with adjusted device parameters, thereby performing identity recognition on the target object based on the identity recognition information collected by the current acquisition device. The technical solution of this application embodiment can improve the identity recognition efficiency and the identity recognition success rate.

Description

Technical Field

[0001] This application relates to the field of computers, and more specifically, to an identity recognition method and apparatus, electronic device, storage medium, and program product. Background Technology

[0002] In the process of identity recognition, it is necessary to collect the identity information of the person to be identified through a data acquisition device, and then identify the person based on the collected identity information. To improve the quality of the collected identity information, the device parameters need to be adjusted. For example, in the process of identity recognition based on palmprint feature data, it is necessary to adjust device parameters such as the camera's exposure time to capture clear palmprint data.

[0003] In related technologies, the device parameters of the acquisition device are usually adjusted according to the light intensity of the environment in which the acquisition device is located. However, determining the device parameters based on light intensity takes a long time, which delays the device parameter adjustment process and reduces the efficiency of identity recognition. Furthermore, since there are differences between different objects, the matching degree between the device parameters adjusted according to light intensity and the current object to be identified is low, resulting in low quality of the identity recognition information of the current object to be identified, and thus reducing the success rate of identity recognition. Summary of the Invention

[0004] The embodiments of this application provide an identity recognition method and apparatus, electronic device, storage medium, and program product, which can improve identity recognition efficiency and success rate.

[0005] According to one aspect of the embodiments of this application, an identity recognition method is provided, the method comprising:

[0006] Obtain the historical device parameters corresponding to the target object to be identified; wherein, the historical device parameters are the device parameters used to collect identity recognition information during the historical identity recognition process of the target object;

[0007] Adjust the current data acquisition device parameters based on the historical device parameters;

[0008] The current acquisition device, after adjusting its parameters, acquires the identity information of the target object.

[0009] The target object is identified based on the identity information collected by the current acquisition device.

[0010] According to one aspect of the embodiments of this application, an identity recognition device is provided, the device comprising:

[0011] The acquisition module is configured to acquire historical device parameters corresponding to the target object to be identified; wherein, the historical device parameters are the device parameters used to collect identity recognition information during the historical identity recognition process of the target object;

[0012] The adjustment module is configured to adjust the device parameters of the current acquisition device based on the historical device parameters.

[0013] The acquisition module is configured to acquire the identity information of the target object through the current acquisition device after adjusting the device parameters;

[0014] The identification module is configured to identify the target object based on the identification information collected by the current acquisition device.

[0015] In an exemplary embodiment, the acquisition module is configured to: if a target object to be identified is detected, acquire the current identification information of the target object; search for historical identification information that matches the current identification information from a historical device parameter set; wherein the historical device parameter set contains a mapping relationship between historical identification information and historical device parameters of different objects; and acquire the historical device parameters corresponding to the searched historical identification information.

[0016] In an exemplary embodiment, the device further includes a storage module configured to: acquire historical identification information of the target object during the historical identification process of the target object, and acquire identification information through a historical acquisition device; acquire device parameters of the historical acquisition device used to acquire identification information, and associate and store the historical identification information of the target object and the acquired device parameters in the historical device parameter set.

[0017] In an exemplary embodiment, the storage module is configured to: identify the target object based on the identification information collected by the historical acquisition device; if the identity information of the target object is successfully identified based on the identification information collected by the historical acquisition device, then obtain the device parameters of the historical acquisition device when collecting the identification information, and associate and store the historical identification information of the target object and the obtained device parameters of the historical acquisition device in the historical device parameter set.

[0018] In an exemplary embodiment, the storage module is configured to: if the identity information corresponding to the identity information collected by the historical acquisition device is successfully identified, then obtain the successful identification time; calculate the time difference between the acquisition time of the historical identification information of the target object and the successful identification time; if the time difference is less than a set time difference threshold, then use the successfully identified identity information as the identity information of the target object, and obtain the device parameters when the historical acquisition device collected the identity information.

[0019] In an exemplary embodiment, the storage module is configured to associate and store the historical identification information of the target object, the device parameters of the historical acquisition device, and the identity information of the target object successfully identified based on the identity recognition information acquired by the historical acquisition device into the historical device parameter set.

[0020] In an exemplary embodiment, given that the historical device parameter set contains a mapping relationship between historical identification information, historical device parameters, and identity information of different objects, the identification module is configured to: search for target identity information corresponding to the current identification information from the historical device parameter set; search for identity recognition information corresponding to the target identity information from the identity information set, and compare the searched identity recognition information with the identity recognition information collected by the current acquisition device; if the searched identity recognition information matches the identity recognition information collected by the current acquisition device, then the target identity information is used as the identity information of the target object.

[0021] In an exemplary embodiment, the acquisition module is configured to: if a target object to be identified is detected, acquire the current identification information of the target object through the current acquisition device; wherein the current identification information is of a different type than the identity recognition information.

[0022] In an exemplary embodiment, when the current acquisition device includes a camera, the adjustment module is configured to: increase the field of view of the camera according to a set default device parameter, so as to acquire the identification information of the next object to be identified according to the camera with the increased field of view.

[0023] In an exemplary embodiment, the identification module is further configured to: if the identity information of the target object is not identified based on the identity information collected by the current acquisition device within a specified time period, then readjust the device parameters of the current acquisition device according to a set adjustment strategy; re-acquire the identity information of the target object using the current acquisition device after the device parameters have been readjusted; and perform identity identification on the target object based on the re-acquired identity information.

[0024] In an exemplary embodiment, where the current acquisition device includes a color camera and an infrared camera, the acquisition module is configured to: acquire palm print feature data of the target object through the color camera with adjusted device parameters, and acquire palm vein feature data of the target object through the infrared camera with adjusted device parameters; fuse the palm print feature data and the palm vein feature data to obtain palm feature data of the target object, and use the palm feature data as the identity recognition information of the target object acquired by the current acquisition device.

[0025] According to one aspect of the embodiments of this application, an electronic device is provided, comprising:

[0026] One or more processors;

[0027] A storage device for storing one or more computer programs that, when executed by one or more processors, enable the electronic device to perform the identification method as described above.

[0028] According to one aspect of the embodiments of this application, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor of an electronic device, causes the electronic device to implement the identification method as described above.

[0029] According to one aspect of the embodiments of this application, a computer program product is provided, including a computer program that, when executed by a processor, implements the identity recognition method as described above.

[0030] In the technical solution provided in the embodiments of this application, when it is necessary to identify the target object, the historical device parameters corresponding to the target object are first obtained. These historical device parameters are the device parameters used to collect identification information during the historical identification process of the target object. Therefore, the historical device parameters have a high degree of matching with the target object. Adjusting the device parameters of the current acquisition device according to the historical device parameters can not only reduce the time spent in the device parameter adjustment process, thereby improving the identification efficiency, but also improve the matching degree between the adjusted device parameters and the target object. This allows the current acquisition device, after adjusting the device parameters, to accurately collect the identification information of the target object, so as to identify the target object based on the identification information collected by the current acquisition device, thereby improving the identification success rate.

[0031] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0032] Figure 1This is a schematic diagram illustrating an implementation environment as shown in an exemplary embodiment of this application;

[0033] Figure 2 This is a flowchart illustrating an exemplary embodiment of the identity recognition method of this application;

[0034] Figure 3 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application;

[0035] Figure 4 This is a schematic diagram illustrating an identity recognition method as shown in another exemplary embodiment of this application;

[0036] Figure 5 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application;

[0037] Figure 6 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application;

[0038] Figure 7 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application;

[0039] Figure 8 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application;

[0040] Figure 9 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application;

[0041] Figure 10 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application;

[0042] Figure 11 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application;

[0043] Figure 12 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application;

[0044] Figure 13 This is a schematic diagram illustrating an identity recognition method according to an exemplary embodiment of this application;

[0045] Figure 14 This is a flowchart illustrating an exemplary embodiment of the identity recognition method of this application;

[0046] Figure 15 This is a schematic diagram illustrating a historical facial feature dataset, as shown in an exemplary embodiment of this application;

[0047] Figure 16This is a schematic diagram illustrating exposure parameters in an exemplary embodiment of this application;

[0048] Figure 17 This is a block diagram illustrating an identity recognition method in an exemplary embodiment of this application;

[0049] Figure 18 This is a schematic diagram illustrating a set of historical exposure parameters, as shown in another exemplary embodiment of this application;

[0050] Figure 19 This is a schematic diagram of the structure of an identity recognition device shown in another exemplary embodiment of this application;

[0051] Figure 20 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown. Detailed Implementation

[0052] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0053] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0054] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily need to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0055] It should also be noted that "multiple" as mentioned in this application refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0056] The technical solutions of the embodiments of this application are described in detail below:

[0057] In related technologies, the device parameters of the acquisition device are usually adjusted based on the light intensity of the environment in which the acquisition device is located. However, determining the device parameters based on light intensity takes a long time, thus delaying the parameter adjustment process and reducing the efficiency of identity recognition. Furthermore, due to the differences between different objects, the matching degree between the device parameters adjusted according to light intensity and the current object to be identified is low, resulting in low quality of the identity recognition information of the current object to be identified, thereby reducing the success rate of identity recognition. Based on this, embodiments of this application provide an identity recognition method and apparatus, electronic device, storage medium, and program product, which can improve the efficiency and success rate of identity recognition.

[0058] Please see Figure 1 , Figure 1 This is a schematic diagram of an implementation environment related to this application, which includes a terminal device 110 and a server 120. The terminal device 110 and the server 120 communicate with each other via a wired or wireless network. The terminal device 110 can upload its own data to the server 120 and can also retrieve data from the server 120.

[0059] Among them, terminal device 110 may include, but is not limited to, smartphones, tablets, laptops, computers, smart voice interaction devices, smart home appliances, vehicle terminals, aircraft, payment devices, etc.

[0060] Server 120 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. This document does not impose any restrictions on this.

[0061] It should be noted that, Figure 1 The number of terminal devices 110 and servers 120 is merely illustrative; any number of terminal devices 110 and servers 120 can be used as needed.

[0062] In an exemplary embodiment, the identity recognition method provided in the embodiments of this application can be executed by a terminal device 110. For example, during the process of recognizing a target object, the terminal device 110 can first obtain historical device parameters corresponding to the target object, wherein the historical device parameters are the device parameters used to collect identity recognition information during the target object's historical identity recognition process; then, it adjusts the device parameters of the current collection device according to the historical device parameters, so as to collect the target object's identity recognition information through the current collection device with adjusted device parameters, thereby recognizing the target object based on the identity recognition information collected by the current collection device; since the historical device parameters corresponding to the target object are the device parameters used to collect identity recognition information during the target object's historical identity recognition process, the historical device parameters have a high degree of matching with the target object. Adjusting the device parameters of the current collection device according to the historical device parameters can not only reduce the time consumed in the device parameter adjustment process and improve the identity recognition efficiency, but also improve the matching degree between the adjusted device parameters and the target object, thereby improving the quality of the collected target object's identity recognition information and thus improving the identity recognition success rate.

[0063] In another exemplary embodiment, server 120 may have functions similar to terminal device 110 to execute the identity recognition method provided in this application embodiment. For example, during the process of recognizing the target object, server 120 may first obtain historical device parameters corresponding to the target object, wherein the historical device parameters are device parameters used to collect identity recognition information during the target object's historical identity recognition process; then, it adjusts the device parameters of the current collection device according to the historical device parameters, so as to collect the target object's identity recognition information through the current collection device with adjusted device parameters, thereby recognizing the target object based on the identity recognition information collected by the current collection device.

[0064] In another exemplary embodiment, the terminal device 110 and the server 120 may also jointly execute the identity recognition method provided in the embodiments of this application. For example, during the process of recognizing the target object to be identified, the terminal device 110 may first obtain historical device parameters corresponding to the target object, wherein the historical device parameters are the device parameters used to collect identity recognition information during the historical identity recognition process of the target object; then, it adjusts the device parameters of the current collection device according to the historical device parameters, so as to collect the identity recognition information of the target object through the current collection device with adjusted device parameters, and sends the identity recognition information of the target object collected by the current collection device to the server 120. The server 120 parses the identity recognition information of the target object to perform identity recognition on the target object, and then sends the recognized identity information of the target object to the terminal device 110.

[0065] It should be noted that the identity recognition method provided in the embodiments of this application can be applied to any scenario requiring identity verification or recognition. For example, in one example, it can be applied to a payment scenario, where payment is made based on the identity information of the target object after the target object's identity information is recognized. The embodiments of this application involve user-related data such as identity recognition information. When the method of this application is applied to specific products or technologies, user permission or consent is always obtained, and the extraction, use, and processing of related data comply with local security standards and local laws and regulations.

[0066] See Figure 2 , Figure 2 This is a flowchart illustrating an exemplary embodiment of an identity recognition method according to this application. The method can be applied to... Figure 1 The implementation environment shown can be composed of Figure 1 The terminal device 110 in the implementation environment shown can execute this, or it can be performed by... Figure 1 The server 120 in the implementation environment shown can perform the operation, or it can be performed by... Figure 1 The terminal device 110 and server 120 in the implementation environment shown are executed together.

[0067] like Figure 2 As shown, in an exemplary embodiment, the identity recognition method may include steps S210-S240, which are described in detail below:

[0068] Step S210: Obtain the historical device parameters corresponding to the target object to be identified; wherein, the historical device parameters are the device parameters used to collect identity recognition information during the historical identity recognition process of the target object.

[0069] The target object refers to the object whose identity is to be identified, and the type of the object includes, but is not limited to, at least one of the following: human, animal, etc.

[0070] Identity recognition information refers to information used to identify the identity of an object. Different objects have different identity recognition information, and the identity of an object can be identified based on the identity recognition information. For example, identity recognition information includes, but is not limited to, at least one of the following: biometric information, fingerprint information, palm print information, palm vein information, iris information, voice timbre information, and hand features. Identity recognition card information refers to the information collected from the identity recognition card used to prove the identity of an object, including but not limited to the image of the identity recognition card.

[0071] Device parameters used for collecting identity verification information refer to parameters specific to the collection device that can affect the collection of identity verification information. The collection device is used to collect identity verification information. The types of collection devices include, but are not limited to, cameras and audio pickup devices (e.g., microphones). Cameras include, but are not limited to, color cameras and infrared cameras. For example, a color camera can collect facial images, fingerprint images, palm print images, iris images, and hand images to extract facial feature information, fingerprint feature information, palm print feature information, iris feature information, timbre feature information, and hand feature information, respectively. An infrared camera can collect palm vein infrared images to extract palm vein feature information. An audio pickup device can collect audio to extract timbre feature information. Different types of acquisition devices have different parameters for collecting identity recognition information. If the acquisition device is a color camera, its corresponding device parameters include, but are not limited to, exposure parameters. Among these, the exposure parameters of a color camera include, but are not limited to, at least one of the following: exposure time, focal length, field of view, gain parameters of the image signal processing (ISP) unit, and gain parameters of the photosensitive chip (sensor). If the acquisition device is an infrared camera, its corresponding device parameters include, but are not limited to, exposure parameters. Among these, the exposure parameters of an infrared camera include, but are not limited to, at least one of the following: exposure time, focal length, field of view, gain parameters of the image signal processing unit, gain parameters of the photosensitive chip, and current of the infrared lamp. If the acquisition device is an audio pickup device, its corresponding device parameters include, but are not limited to, at least one of the following: volume and angle of audio acquisition.

[0072] In the process of historical identification of a target object, it is necessary to collect the target object's identification information through historical acquisition devices in order to identify the target object based on the collected identification information. In order to improve the efficiency of identification, the device parameters of the historical acquisition devices when collecting the target object's identification information can be stored as the historical device parameters corresponding to the target object. When it is necessary to identify the target object now, the stored historical device parameters corresponding to the target object can be retrieved first.

[0073] Optionally, before step S210, an authorization instruction from the target object for the identity recognition function may be received, and step S210 may be executed after the authorization instruction from the target object is received.

[0074] Step S220: Adjust the current acquisition device parameters according to historical device parameters.

[0075] The current data collection device refers to the device used to collect the identity information of the target object during the current identity verification process. Optionally, the current data collection device and the historical data collection device can be the same device, or they can be different devices.

[0076] Different objects have different identification information, and their operating habits during the identification information collection process also differ. For example, different objects have different hand sizes, and during the collection of palmprint feature data, some users' palms are closer to the camera, while others are farther away. Therefore, in order to improve the matching degree between the adjusted device parameters and the target object, after obtaining the historical device parameters corresponding to the target object, the device parameters of the current collection device can be adjusted according to these historical device parameters. Since the historical device parameters corresponding to the target object are the device parameters used to collect identification information in the target object's past identification process, they are more in line with the target object's operating habits and identification information. Therefore, adjusting the device parameters of the current collection device according to these historical device parameters can improve the matching degree between the adjusted device parameters and the target object, thereby improving the quality of the target object's identification information collected by the adjusted current collection device.

[0077] One specific method for adjusting the current acquisition device parameters based on historical device parameters is to adjust the current acquisition device parameters so that the adjusted current acquisition device parameters match the historical device parameters.

[0078] Optionally, if multiple historical device parameters corresponding to the target object are obtained, the device parameters of the current acquisition device can be adjusted according to the average value of the multiple historical device parameters corresponding to the target object; or, the historical device parameters corresponding to the most recent historical identity recognition process can be found from the multiple historical device parameters corresponding to the target object, and the device parameters of the current acquisition device can be adjusted according to the historical device parameters corresponding to the most recent historical identity recognition process.

[0079] Step S230: The current acquisition device, after adjusting the device parameters, acquires the identity information of the target object.

[0080] After adjusting the device parameters of the current acquisition device, the identification information of the target object can be collected through the current acquisition device.

[0081] Optionally, during the identity recognition process, identity recognition information needs to be collected. Before step S230, an authorization instruction from the target object for the collection of identity recognition information can be received. After receiving the authorization instruction from the target object, the identity recognition information of the target object is collected through the current collection device.

[0082] Step S240: Identify the target object based on the identity information collected by the current acquisition device.

[0083] After collecting the target object's identity information through the current acquisition device, the target object can be identified based on the identity information collected by the current acquisition device.

[0084] The specific method for identifying the target object based on the identity information collected by the current acquisition device can be flexibly set according to actual needs. In an exemplary embodiment, an identity information set can be set up. This identity information set serves as a standard for identity recognition and includes the identity information of different objects and the corresponding identity recognition information. After the identity information of the target object is collected by the current acquisition device, the identity information matching the target object's identity information collected by the current acquisition device can be searched from the identity information set. The identity information corresponding to the searched identity information is then used as the target object's identity information. The identity information in the identity information set can be pre-collected identity information used as the object's identity recognition standard.

[0085] exist Figure 2 In the illustrated embodiment, when it is necessary to identify the target object, the historical device parameters corresponding to the target object are first obtained. These historical device parameters are the device parameters used to collect identification information during the target object's historical identification process. Therefore, the historical device parameters have a high degree of matching with the target object. Adjusting the device parameters of the current acquisition device based on these historical device parameters can not only reduce the time spent on the device parameter adjustment process, thereby improving the identification efficiency, but also improve the matching degree between the adjusted device parameters and the target object. This allows the current acquisition device, after adjusting the device parameters, to accurately collect the target object's identification information, thereby improving the identification success rate.

[0086] In one exemplary embodiment, see Figure 3 , Figure 3 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application. This method can be applied to... Figure 1 The implementation environment shown can be composed of Figure 1 The terminal device 110 in the implementation environment shown can execute this, or it can be performed by... Figure 1 The server 120 in the implementation environment shown can perform the operation, or it can be performed by... Figure 1 The terminal device 110 and server 120 in the implementation environment shown are executed together.

[0087] like Figure 3 As shown, the method includes steps S310-S330 and steps S220-S240, wherein the detailed description of steps S310-S330 is as follows:

[0088] Step S310: If a target object to be identified is detected, the current identification information of the target object is obtained.

[0089] It should be noted that object identification information refers to information that can distinguish an object from other objects, thereby identifying the object. The types of object identification information include, but are not limited to, at least one of biometric information, identification card information used to prove the identity of the object, etc. In order to distinguish it from the object's identification information, the types of object identification information and object identification information are different. For example, in one example, the object identification information is the object's facial feature information, and the object's identification information is the object's palm print feature information.

[0090] If a target object to be identified is detected, the device parameters of the current acquisition device need to be adjusted. To determine how to adjust the device parameters, the current identification information of the target object can be obtained first. The current identification information of the target object refers to the currently acquired identification information of the target object.

[0091] The specific method for detecting the target object to be identified can be flexibly set according to actual needs. Optionally, in one example, if an object wants to be identified, its distance from the data collection device is usually relatively close. Therefore, objects whose distance from the data collection device is less than a set distance threshold can be used as the target object to be identified. Alternatively, in another example, if an object wants to be identified, it usually moves towards the data collection device. Therefore, objects that move towards the data collection device and whose distance from the data collection device is less than a set distance threshold can be used as the target object to be identified. The specific value of the set distance threshold can be flexibly set according to actual needs, for example, set to 1 meter, 50 centimeters, 20 centimeters, etc.

[0092] Step S320: Search for historical identification information that matches the current identification information from the historical device parameter set; wherein, the historical device parameter set contains the mapping relationship between historical identification information and historical device parameters of different objects.

[0093] The historical device parameter set contains the mapping relationship between the historical identification information of different objects and the historical device parameters. The historical identification information of an object refers to the identification information of the object obtained during the historical identification process.

[0094] In order to obtain the historical device parameters of the target object, the historical identification information that matches the current identification information of the target object can be searched from the historical device parameter set. Then, the historical device parameters corresponding to the historical identification information that matches the current identification information can be used as the historical device parameters of the target object.

[0095] If multiple acquisition devices are involved, in an optional example, considering the differences between different acquisition devices, in order to improve the matching degree between the historical device parameters corresponding to the target object and the current identification information, and reduce the amount of data processing, in step S320, historical identification information that matches the current identification information of the target object can be searched from the historical device parameter set corresponding to the current acquisition device, so that the historical device parameters corresponding to the searched historical identification information are used as the historical device parameters corresponding to the target object. The historical device parameter set corresponding to the current acquisition device includes the historical device parameters of the current acquisition device (i.e., the device parameters used by the current acquisition device to collect identification information during the historical identification process), and the historical identification information corresponding to the device parameters. Alternatively, in another optional example, in step S320, historical identification information that matches the current identification information of the target object can also be searched from the historical device parameter sets corresponding to multiple acquisition devices. The historical device parameter sets corresponding to multiple acquisition devices include the historical device parameters corresponding to each of the multiple acquisition devices, and the historical identification information corresponding to the historical device parameters.

[0096] If the data acquisition devices are deployed on terminal devices and include multiple terminal devices, in an optional example, to improve security and reduce network transmission speed, a historical device parameter set can be set for each terminal device. Each historical device parameter set only contains the historical device parameters of the data acquisition devices deployed on the corresponding terminal device, as well as the identification information corresponding to those historical device parameters. That is, different terminal devices will not share the historical device parameters of the data acquisition devices. For example, if terminal device a includes data acquisition device b1, and terminal device c includes data acquisition devices b2 and b3, then the historical device parameter set corresponding to terminal device a includes the historical device parameters of data acquisition device b1, as well as the historical device parameters corresponding to those historical device parameters. Identification information; the historical device parameter set corresponding to terminal device c includes the historical device parameters corresponding to acquisition devices b2 and b3 respectively, and the historical identification information corresponding to the historical device parameters; under this condition, in step S320, historical identification information matching the current identification information of the target object can be searched from the historical device parameter set corresponding to the terminal device to which the current acquisition device belongs, so as to use the historical device parameters corresponding to the searched historical identification information as the historical device parameters corresponding to the target object. The historical device parameter set corresponding to each terminal device can be stored in the memory included in the terminal device (i.e., local storage), or it can be stored in a cloud database. Alternatively, in another example, in step S320, historical identification information matching the current identification information of the target object can be searched from the historical device parameter sets corresponding to multiple terminal devices. The historical device parameter sets corresponding to multiple terminal devices include the historical device parameters corresponding to the acquisition devices deployed on multiple devices respectively, and the historical identification information corresponding to the historical device parameters. That is, different terminal devices will share the historical device parameters of the acquisition devices.

[0097] Step S330: Obtain the historical device parameters corresponding to the found historical identifier information.

[0098] After finding historical identification information that matches the current identification information of the target object, it indicates that the target object has been identified before. The found historical identification information is the historical identification information of the target object. Therefore, the historical device parameters corresponding to the found historical identification information are used as the historical device parameters corresponding to the target object.

[0099] It should be noted that, Figure 3 The specific implementation details of steps S220-S240 shown can be found in [reference]. Figure 2 Steps S220-S240 shown are not repeated here.

[0100] exist Figure 3In the illustrated embodiment, by setting a historical device parameter set containing the mapping relationship between historical identification information and historical device parameters of different objects, the historical device parameters corresponding to the target object can be found from the historical device parameter set based on the current identification information of the target object, thereby improving the search speed and the accuracy of the searched historical device parameters.

[0101] In one exemplary embodiment, see Figure 4 , Figure 4 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application. This method can be applied to... Figure 1 The implementation environment shown can be composed of Figure 1 The terminal device 110 in the implementation environment shown can execute this, or it can be performed by... Figure 1 The server 120 in the implementation environment shown can perform the operation, or it can be performed by... Figure 1 The terminal device 110 and server 120 in the implementation environment shown are executed together.

[0102] like Figure 4 As shown, the method includes steps S410-S420, S310-S330, and S220-S240. The detailed descriptions of steps S410-S420 are as follows:

[0103] Step S410: In the historical identity recognition process of the target object, the historical identification information of the target object is obtained, and the identity recognition information is collected through the historical acquisition device.

[0104] Before step S320, during the historical identity recognition process of the target object, the identification information of the target object in this historical identity recognition process can be obtained, that is, the historical identification information of the target object, and the identity recognition information can be collected through the historical acquisition device.

[0105] Step S420: Obtain the device parameters of the historical acquisition device used to collect identity recognition information, and associate and store the historical identification information of the target object with the acquired device parameters in the historical device parameter set.

[0106] To facilitate rapid adjustment of the acquisition device parameters during subsequent identification of the target object, thereby improving the quality of the acquired identification information, the device parameters used by the acquisition device in the past for collecting identification information can be obtained. Specifically, the historical device parameters corresponding to the target object can be acquired, and then the historical identification information of the target object and these device parameters can be associated and stored in a historical device parameter set. This facilitates the retrieval of the historical device parameters corresponding to the target object from the historical device parameter set during the candidate identification process, allowing for rapid adjustment of the acquisition device parameters based on the historical device parameters corresponding to the target object.

[0107] Optionally, to avoid situations where the quality of the target object's identity recognition information collected by historical acquisition devices is low, resulting in the current acquisition device's acquisition information being of low quality after adjusting the device parameters based on the target object's historical device parameters, thus failing to identify the target object's identity, before step S420, it can be determined whether the identity recognition information collected by historical acquisition devices meets the set conditions. If yes, then step S420 is executed; that is, only if the identity recognition information collected by historical acquisition devices meets the set conditions will the device parameters used by the historical acquisition devices for collecting identity recognition information be stored in the historical device parameter set; otherwise, the storage of the device parameters used by the historical acquisition devices for collecting identity recognition information in the historical device parameter set is prohibited. The specific content of the set conditions can be flexibly set according to actual needs. For example, in one example, the set conditions include: the quality parameters of the identity recognition information collected by historical acquisition devices are better than the set quality parameters. Here, quality parameters refer to parameters that can characterize the quality of identity recognition information. For example, assuming the type of identity recognition information is an image, quality parameters include, but are not limited to, image sharpness, resolution, signal-to-noise ratio, etc. In another example, the set conditions include: successfully identifying the identity information of the target object based on the identity recognition information of the target object collected by the historical acquisition device. For details, please refer to the description in the subsequent embodiments, which will not be repeated here.

[0108] Optionally, to reduce the capacity of the historical device parameter set, during the process of associating and storing the historical identification information of the target object and the acquired device parameters into the historical device parameter set, it can be first determined whether the number of historical device parameters of the target object contained in the historical device parameter set has reached a set threshold. If not, the historical identification information of the target object and the acquired device parameters can be directly associated and stored into the historical device parameter set. If so, the historical device parameters corresponding to the target object that were first stored in the historical device parameter set are deleted from the historical device parameter set, and the historical identification information of the target object and the acquired device parameters are associated and stored into the historical device parameter set. This limits the number of historical device parameters corresponding to the target object contained in the historical device parameter set and continuously updates the historical device parameters corresponding to the target object in the historical device parameter set. The specific value of the set threshold can be flexibly set according to actual needs, such as 3, 4, 5, etc.

[0109] It should be noted that, Figure 4 The specific implementation details of steps S220-S240 shown can be found in [reference]. Figure 2 Steps S220-S240 are shown. Figure 4 The specific implementation details of steps S310-S330 shown can be found in [reference]. Figure 3 Steps S310-S330 shown are not repeated here.

[0110] exist Figure 4 In the illustrated embodiment, during the historical identification process of the target object, historical identification information of the target object is obtained, and identification information is collected through a historical acquisition device. The device parameters used by the historical acquisition device to collect identification information are obtained, and the historical identification information of the target object and the obtained device parameters are associated and stored in a historical device parameter set, thereby realizing the storage of historical device parameters and historical identification information.

[0111] In one exemplary embodiment, see Figure 5 , Figure 5 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application. This method can be applied to... Figure 1 The implementation environment shown can be composed of Figure 1 The terminal device 110 in the implementation environment shown can execute this, or it can be performed by... Figure 1 The server 120 in the implementation environment shown can perform the operation, or it can be performed by... Figure 1 The terminal device 110 and server 120 in the implementation environment shown are executed together.

[0112] like Figure 5As shown, the method includes steps S410, S510-S520, S310-S330, and S220-S240. The detailed descriptions of steps S510-S520 are as follows:

[0113] Step S510: Identify the target object based on the identity information collected by the historical data collection device.

[0114] In the historical identification process of a target object, after identity information is collected through historical acquisition devices, the target object needs to be identified based on this historical information. The specific method for identifying the target object based on historical information is similar to the method for identifying the target object based on current information, and will not be elaborated upon here.

[0115] Step S520: If the identity information of the target object is successfully identified based on the identity recognition information collected by the historical acquisition device, the device parameters of the historical acquisition device when collecting the identity recognition information are obtained, and the historical identification information of the target object and the obtained device parameters of the historical acquisition device are associated and stored in the historical device parameter set.

[0116] After identifying the target object based on the identification information collected by historical acquisition devices, if the target object's identity information is successfully identified, the device parameters of the historical acquisition devices when they collected the identification information are obtained. The historical identification information of the target object and these device parameters are then associated and stored in a historical device parameter set, facilitating subsequent adjustment of the current acquisition device's parameters based on these parameters. In other words, the set condition includes successfully identifying the target object's identity information based on the identification information collected by historical acquisition devices. Specifically, the device parameters of the historical acquisition devices at the time of successful identification can be obtained and stored in the historical device parameter set, or the device parameters of the historical acquisition devices at the time of successful identification can be obtained and stored in the historical device parameter set.

[0117] Optionally, if the identity information of the target object is not identified, the acquisition of device parameters when the historical acquisition device collected identity information can be prohibited, so as to prevent the storage of such device parameters in the historical device parameter set.

[0118] It should be noted that, Figure 5 The specific implementation details of steps S220-S240 shown can be found in [reference]. Figure 2 Steps S220-S240 are shown. Figure 5 The specific implementation details of steps S310-S330 shown can be found in [reference]. Figure 3 Steps S310-S330 are shown. Figure 5 For details on the specific implementation of step S410 shown, please refer to Figure 4 Step S410 shown will not be repeated here.

[0119] exist Figure 5 In the illustrated embodiment, the historical device parameter set stores the device parameters of historical acquisition devices under successful identity recognition conditions, thereby improving the success rate of identity recognition after adjusting the current acquisition device based on the historical device parameters in the historical device parameter set.

[0120] In one exemplary embodiment, see Figure 6 , Figure 6 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application. This method can be applied to... Figure 1 The implementation environment shown can be composed of Figure 1 The terminal device 110 in the implementation environment shown can execute this, or it can be performed by... Figure 1 The server 120 in the implementation environment shown can perform the operation, or it can be performed by... Figure 1 The terminal device 110 and server 120 in the implementation environment shown are executed together.

[0121] like Figure 6 As shown, the method includes steps S410, S510, S610-S640, S310-S330, and S220-S240. The detailed descriptions of steps S610-S640 are as follows:

[0122] Step S610: If the identity information corresponding to the identity information collected by the historical collection device is successfully identified, the successful identification time is obtained.

[0123] To avoid situations where historical identification information and identity recognition information do not belong to the same object during this identity recognition process, if the corresponding identity information is successfully recognized based on the identity recognition information collected by the historical collection device, the time when the corresponding identity information was successfully recognized based on the identity recognition information collected by the historical collection device can be obtained first, i.e., the successful recognition time.

[0124] Step S620: Calculate the time difference between the acquisition time of the historical identification information of the target object and the successful identification time.

[0125] After obtaining the successful identification time, the time difference between the acquisition time of the target object's historical identification information and the successful identification time can be calculated.

[0126] Step S630: If the time difference is less than the set time difference threshold, the successfully identified identity information is used as the identity information of the target object, and the device parameters when the historical collection device collected identity recognition information are obtained.

[0127] Setting a time difference threshold is a standard used to determine whether the historical identification information obtained during the current historical identification process and the successfully identified identification information belong to the same object. Its specific value can be flexibly set according to actual needs, for example, it can be set to 2 seconds, 3 seconds, 10 seconds, etc.

[0128] In this historical identity recognition process, if the time difference between the acquisition time of the target object's historical identification information and the successful identification time of the identity information is less than the set time difference threshold, it indicates that the historical identification information acquired and the identity information successfully identified belong to the same object in this historical identity recognition process. Therefore, the identified identity information can be used as the target object's identity information, and the device parameters when the historical acquisition device collected the identity recognition information can be obtained.

[0129] Optionally, if the time difference between the acquisition time of historical identification information and the successful identification time is greater than or equal to the set time difference threshold, it indicates that the historical identification information acquired during this historical identification process is likely to belong to different objects than the successfully identified identification information. Therefore, it is possible to prohibit the acquisition of device parameters when the historical acquisition device collects identification information, thereby prohibiting the association of historical identification information with the device parameters and storing it in the historical device parameter set.

[0130] Step S640: The historical identification information of the target object and the acquired historical acquisition device parameters are associated and stored in the historical device parameter set.

[0131] When the device parameters of the historical data collection device are obtained, the historical identification information of the target object and the obtained device parameters are associated and stored in the historical device parameter set.

[0132] It should be noted that, Figure 6 The specific implementation details of steps S220-S240 shown can be found in [reference]. Figure 2 Steps S220-S240 are shown. Figure 6 The specific implementation details of steps S310-S330 shown can be found in [reference]. Figure 3 Steps S310-S330 are shown. Figure 6 For details on the specific implementation of step S410 shown, please refer to Figure 4 Step S410 shown, Figure 6 For details on the specific implementation of step S510 shown, please refer to Figure 5Step S510 shown will not be repeated here.

[0133] exist Figure 6 In the illustrated embodiment, during the historical identity recognition process of the target object, if the identity recognition is successful and the time difference between the acquisition time of the historical identification information of the target object and the successful recognition time is small, the historical identification information of the target object and the device parameters of the historical acquisition device are associated and stored in the historical device parameter set. This avoids the situation where the historical identification information and historical device parameters with mapping relationship correspond to different objects, thereby improving the success rate of identity recognition.

[0134] In one exemplary embodiment, see Figure 7 , Figure 7 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application. This method can be applied to... Figure 1 The implementation environment shown can be composed of Figure 1 The terminal device 110 in the implementation environment shown can execute this, or it can be performed by... Figure 1 The server 120 in the implementation environment shown can perform the operation, or it can be performed by... Figure 1 The terminal device 110 and server 120 in the implementation environment shown are executed together.

[0135] like Figure 7 As shown, the method includes steps S410, S510, S710-S720, S310-S330, and S220-S240. The detailed descriptions of steps S710-S720 are as follows:

[0136] Step S710: If the identity information of the target object is successfully identified based on the identity recognition information collected by the historical acquisition device, then obtain the device parameters when the historical acquisition device collected the identity recognition information.

[0137] If the identity information of the target object is successfully identified based on the identity recognition information collected by the historical data collection device, then the device parameters of the historical data collection device when collecting the identity recognition information can be obtained.

[0138] Step S720: The historical identification information of the target object, the device parameters of the historical acquisition device, and the identity information of the target object successfully identified based on the identity recognition information acquired by the historical acquisition device are associated and stored in the historical device parameter set.

[0139] After identifying the target object based on the identification information collected by the historical acquisition devices, if the target object's identity information is successfully identified, the target object's historical identification information, the acquired device parameters, and the successfully identified target object's identity information can be associated and stored in the historical device parameter set.

[0140] It should be noted that, Figure 7 The specific implementation details of steps S220-S240 shown can be found in [reference]. Figure 2 Steps S220-S240 are shown. Figure 7 The specific implementation details of steps S310-S330 shown can be found in [reference]. Figure 3 Steps S310-S330 are shown. Figure 7 For details on the specific implementation of step S410 shown, please refer to Figure 4 Step S410 shown, Figure 7 For details on the specific implementation of step S510 shown, please refer to Figure 5 Step S510 shown will not be repeated here.

[0141] exist Figure 7 In the illustrated embodiment, the historical identification information of the target object, the device parameters of the acquired historical acquisition device, and the identity information of the successfully identified target object are associated and stored in the historical device parameter set, which enriches the content of the historical device parameter set and improves the success rate of identity recognition based on the historical device parameter set.

[0142] In one exemplary embodiment, see Figure 8 , Figure 8 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application. This method can be applied to... Figure 1 The implementation environment shown can be composed of Figure 1 The terminal device 110 in the implementation environment shown can execute this, or it can be performed by... Figure 1 The server 120 in the implementation environment shown can perform the operation, or it can be performed by... Figure 1 The terminal device 110 and server 120 in the implementation environment shown are executed together.

[0143] like Figure 8 As shown, given that the historical device parameter set contains mapping relationships between historical identification information, historical device parameters, and identity information of different objects, the method includes steps S310-S330, S220-S230, and S810-S830. The detailed descriptions of steps S810-S830 are as follows:

[0144] Step S810: Search for the target identity information corresponding to the current identification information from the historical device parameter set.

[0145] Given that the historical device parameter set contains the mapping relationship between the historical identification information, historical device parameters and identity information of different objects, in order to improve the speed of identifying the target object, we can first search for the identity information corresponding to the current identification information of the target object in the historical device parameter set to obtain the target identity information. That is, we search for the historical identification information that matches the current identification information of the target object in the historical device parameter set, and use the identity information corresponding to the searched historical identification information as the target identity information.

[0146] Step S820: Search for the identity recognition information corresponding to the target identity information from the identity information set, and compare the searched identity recognition information with the identity recognition information collected by the current collection device.

[0147] Since the object's identity information, contained in the historical device parameters, was identified during the object's historical identity recognition process, there is a very high probability that the target object's identity information is the target identity information corresponding to the current identifier information of the target object in the historical device parameter set. To determine whether the target object's identity information is the target identity information, the corresponding identity recognition information can be searched from the identity information set, and then compared with the target object's identity recognition information collected by the current acquisition device. For a description of the identity information set, please refer to the aforementioned embodiments; it will not be repeated here.

[0148] Step S830: If the found identity information matches the identity information collected by the current collection device, then the target identity information is used as the identity information of the target object.

[0149] If the identity information corresponding to the target identity information matches the identity information of the target object collected by the current collection device, the target identity information can be used as the identity information of the target object. This eliminates the need to compare the identity information of the target object collected by the current collection device with the identity information contained in the identity information set separately in order to find the identity information of the target object, thereby improving the efficiency of identity recognition.

[0150] Optionally, if the identity information corresponding to the target identity information does not match the identity information of the target object collected by the current collection device, the identity information collected by the current collection device can be compared with other identity information in the identity information set except for the identity information corresponding to the target identity information in order to find the identity information of the target object.

[0151] It should be noted that, Figure 8 The specific implementation details of steps S220-S230 shown can be found in [reference]. Figure 2Steps S220-S230 are shown. Figure 8 The specific implementation details of steps S310-S330 shown can be found in [reference]. Figure 3 Steps S310-S330 shown are not repeated here.

[0152] exist Figure 8 In the illustrated embodiment, given that the historical device parameter set contains the mapping relationship between historical identification information, historical device parameters, and identity information of different objects, the target identity information corresponding to the current identification information is first searched in the historical device parameter set, and the identity recognition information corresponding to the target identity information is searched in the identity information set. The searched identity recognition information is then compared with the identity recognition information collected by the current acquisition device. If the searched identity recognition information matches the identity recognition information collected by the current acquisition device, the target identity information is used as the identity information of the target object. This not only ensures the accuracy of identity recognition but also improves the efficiency of identity recognition.

[0153] In one exemplary embodiment, see Figure 9 , Figure 9 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application. This method can be applied to... Figure 1 The implementation environment shown can be composed of Figure 1 The terminal device 110 in the implementation environment shown can execute this, or it can be performed by... Figure 1 The server 120 in the implementation environment shown can perform the operation, or it can be performed by... Figure 1 The terminal device 110 and server 120 in the implementation environment shown are executed together.

[0154] like Figure 9 As shown, the method includes steps S910, S320-S330, and S220-S240, wherein step S910 is described in detail below:

[0155] Step S910: If a target object to be identified is detected, the current identification information of the target object is collected through the current acquisition device; wherein, the current identification information is of a different type than the identity recognition information.

[0156] Object identification information and object identity information can be collected by the same data acquisition device. However, to distinguish between them, the types of object identification information and object identity information are different. For example, object identification information may be facial feature data, while object identity information may be hand feature data.

[0157] After detecting the target object to be identified, the current identification information of the target object can be obtained by collecting the identification information of the target object through the current acquisition device.

[0158] It should be noted that, Figure 9 The specific implementation details of steps S220-S240 shown can be found in [reference]. Figure 2 Steps S220-S240 are shown. Figure 9 The specific implementation details of steps S320-S330 shown can be found in [reference]. Figure 3 Steps S320-S330 shown are not repeated here.

[0159] exist Figure 9 In the illustrated embodiment, the identification information and identity recognition information of the object are collected using the same acquisition device, thereby reducing costs.

[0160] In one exemplary embodiment, see Figure 10 , Figure 10 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application. This method can be applied to... Figure 1 The implementation environment shown can be composed of Figure 1 The terminal device 110 in the implementation environment shown can execute this, or it can be performed by... Figure 1 The server 120 in the implementation environment shown can perform the operation, or it can be performed by... Figure 1 The terminal device 110 and server 120 in the implementation environment shown are executed together.

[0161] like Figure 10 As shown, assuming the current acquisition device includes a camera, the method includes steps S910, S320-S330, S220-S240, and S1010. The detailed description of step S1010 is as follows:

[0162] Step S1010: Increase the field of view of the camera according to the default device parameters, so as to collect the identification information of the next object to be identified based on the increased field of view of the camera.

[0163] In the process of identity recognition, the object usually approaches the acquisition device first, and then brings the feature part used for identity recognition closer to the acquisition device to collect identity information. For example, in the process of palm print recognition, the user usually approaches the acquisition device first, and then brings the palm closer to the acquisition device to collect the palm print image. Therefore, when the current acquisition device includes a camera, after the target object is identified based on the image acquired by the camera in step S240, the field of view of the camera can be increased according to the set default device parameters. This makes it easier for the camera with the increased field of view to first detect the next object to be identified, and then collect the identification information of the next object to be identified. After the identification information is collected, the identity recognition information is collected. In other words, under the default conditions (i.e., under conditions not used for collecting identity recognition information), the device parameters of the acquisition device match the set default device parameters, making the field of view of the acquisition device larger.

[0164] Optionally, if the current acquisition device contains multiple cameras, and some of the cameras are used to acquire identification information, then in step S1010, the field of view of only the cameras used to acquire identification information can be increased according to the set default device parameters.

[0165] It should be noted that, Figure 10 The specific implementation details of steps S220-S240 shown can be found in [reference]. Figure 2 Steps S220-S240 are shown. Figure 10 The specific implementation details of steps S320-S330 shown can be found in [reference]. Figure 3 Steps S320-S330 are shown. Figure 10 For details on the specific implementation of step S910 shown, please refer to [link / reference]. Figure 9 Step S910 shown will not be described again here.

[0166] exist Figure 10 In the illustrated embodiment, after identifying the target object based on the identification information collected by the current acquisition device, the field of view of the camera is increased according to the set default device parameters. The camera with the increased field of view is then used to acquire the identification information of the next object to be identified. This not only facilitates the acquisition of the identification information of the object to be identified, but also allows the object to be identified to be discovered in advance and its identification information to be acquired. Furthermore, before the feature part approaches the acquisition device, the corresponding historical device parameters can be found based on the identification information of the object to be identified and the device parameters can be adjusted, thereby improving the efficiency of identification.

[0167] In one exemplary embodiment, see Figure 11 , Figure 11 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application. This method can be applied to... Figure 1 The implementation environment shown can be composed of Figure 1 The terminal device 110 in the implementation environment shown can execute this, or it can be performed by... Figure 1 The server 120 in the implementation environment shown can perform the operation, or it can be performed by... Figure 1 The terminal device 110 and server 120 in the implementation environment shown are executed together.

[0168] like Figure 11 As shown, the method includes steps S210-S240 and steps S1110-S1130, wherein the detailed description of steps S1110-S1130 is as follows:

[0169] Step S1110: If the identity information of the target object is not identified based on the identity recognition information collected by the current acquisition device within the specified time period, the device parameters of the current acquisition device are readjusted according to the set adjustment strategy.

[0170] To ensure efficient identity recognition, a pre-set duration and adjustment strategy are configured. The specific value of the duration can be flexibly set according to actual needs, such as, but not limited to, 10 seconds, 15 seconds, 3 seconds, etc. The adjustment strategy is a pre-set adjustment strategy, the specific content of which can be flexibly set according to actual needs. For example, the adjustment strategy can be to adjust the device parameters based on the ambient brightness, the distance between the object and the device, or the light intensity. If the device includes a camera, the adjustment strategy can also be an automatic exposure (AE) strategy, which is a strategy that automatically adjusts the exposure and gain according to the light intensity to prevent overexposure or underexposure.

[0171] If, after adjusting the current acquisition device parameters based on historical device parameters, the target object's identity information is not successfully identified within a specified time period based on the identity recognition information collected by the adjusted current acquisition device, the current acquisition device parameters can be readjusted according to the set adjustment strategy.

[0172] Step S1120: The current acquisition device, after readjusting the device parameters, re-acquires the identity information of the target object.

[0173] After readjusting the device parameters of the current acquisition device according to the set adjustment strategy, the identity information of the target object can be re-acquired by the current acquisition device with the readjusted device parameters for identity recognition.

[0174] Step S1130: Identify the target object based on the re-collected identity information.

[0175] After the target object's identity information is re-collected, it can be used to identify the target object. For example, the identity information set can be searched for to match the re-collected identity information, and the identity information corresponding to the searched identity information can be used as the target object's identity information.

[0176] It should be noted that, Figure 11 The specific implementation details of steps S210-S240 shown can be found in [reference]. Figure 2 Steps S210-S240 shown will not be repeated here.

[0177] exist Figure 11 In the illustrated embodiment, if the identity information of the target object is not identified based on the identity recognition information collected by the current acquisition device within a specified time period, the device parameters of the current acquisition device are readjusted according to the set adjustment strategy, and the identity of the target object is identified based on the re-acquired identity recognition information, thereby improving the success rate and efficiency of identity recognition.

[0178] In one exemplary embodiment, see Figure 12 , Figure 12 This is a flowchart illustrating an identity recognition method as shown in another exemplary embodiment of this application. This method can be applied to... Figure 1 The implementation environment shown can be composed of Figure 1 The terminal device 110 in the implementation environment shown can execute this, or it can be performed by... Figure 1 The server 120 in the implementation environment shown can perform the operation, or it can be performed by... Figure 1 The terminal device 110 and server 120 in the implementation environment shown are executed together.

[0179] like Figure 12 As shown, under the condition that the current acquisition device includes a color camera and an infrared camera, the method includes steps S210-S220, steps S1210-S1230, and step S240. The detailed description of steps S1210-S1220 is as follows:

[0180] Step S1210: Collect palm print feature data of the target object using a color camera with adjusted device parameters, and collect palm vein feature data of the target object using an infrared camera with adjusted device parameters.

[0181] Given that the current acquisition equipment includes both color and infrared cameras, the device parameters of the infrared and color cameras need to be adjusted according to the historical device parameters corresponding to the target object. Then, the palmprint image of the target object can be acquired through the color camera with adjusted device parameters, and palmprint feature data can be extracted from the palmprint image. Furthermore, the palm vein infrared image of the target object can be acquired through the infrared camera with adjusted device parameters, and palm vein feature data can be extracted from the palm vein infrared image.

[0182] Step S1220: The palm print feature data and palm vein feature data are fused to obtain the palm feature data of the target object, and the palm feature data is used as the identity recognition information of the target object collected by the current acquisition device.

[0183] After obtaining the palmprint and palm vein feature data of the target object, these data can be fused to obtain the target object's hand feature data. This hand feature data can then be used as the target object's identification information, enabling identity verification. For example, see... Figure 13 As shown, a color camera can capture a user's palm print image, and an infrared camera can capture an infrared image of the user's palm veins. Palm print feature data and palm vein feature data are extracted from the palm print image and the palm vein infrared image, respectively. The palm print feature data and palm vein feature data are then fused to obtain palm feature data, which is then used for identity recognition.

[0184] The fusion method can be flexibly set according to actual needs. Optionally, in one example, the weight values ​​corresponding to palm print feature data and palm vein feature data can be preset, and the palm print feature data and palm vein feature data of the target object can be fused according to the weight values ​​of palm print feature data and palm vein feature data to obtain the palm feature data of the target object.

[0185] It should be noted that, Figure 12 The specific implementation details of steps S210-S220 and S240 shown can be found in [reference]. Figure 2 Steps S210-S220 and S240 shown will not be repeated here.

[0186] exist Figure 12 In the illustrated embodiment, palm print feature data and palm vein feature data are collected by a color camera and an infrared camera, respectively. The palm print feature data and palm vein feature data are then fused to obtain palm feature data, which includes both palm print feature data and palm vein feature data, thereby improving the accuracy of identity recognition based on palm feature data.

[0187] See Figure 14 As shown, Figure 14 This is a flowchart illustrating an exemplary embodiment of the identity recognition method of this application. The identity recognition method of this embodiment is applied to an implementation environment including a terminal device and a server. The example given uses an infrared camera and a color camera deployed on the terminal device as the data acquisition devices, facial feature data as the identification information, and hand feature data as the identity recognition information. Figure 14 As shown, the identity recognition method includes steps S1401-S1412, which are described in detail below:

[0188] In step S1401, the terminal device displays the authorization prompt information corresponding to the identity recognition function and receives the authorization instruction from the target object in response to the authorization prompt information.

[0189] The authorization prompt information is used to inform the target that the identity recognition function corresponding to the identity recognition method provided in this application embodiment needs to collect facial feature data, palm print feature data, and palm vein feature data, and prompts the user's permission to use and process facial feature data, palm print feature data, and palm vein feature data in the identity recognition function. If the terminal device receives the authorization instruction from the target user in response to the authorization prompt information, that is, the target user agrees to enable the identity recognition function and authorizes the identity recognition function to collect and process facial feature data, palm print feature data, and palm vein feature data, then the process jumps to step S1402 to perform identity recognition.

[0190] In step S1402, the terminal device acquires the current facial image of the target object through a color camera and extracts the current facial feature data of the target object from the current facial image.

[0191] Because facial images require a larger field of view than palm images, and users typically approach the terminal device first before bringing their palms close to the infrared and color cameras to collect palm feature data, in order to identify target objects for identification in advance and adjust the exposure parameters of the infrared and color cameras before the target object's palms approach the infrared and color cameras, the exposure parameters of the color camera are matched with the default exposure parameters by default (i.e., when not collecting palm feature data). The field of view corresponding to the default exposure parameters is larger than the field of view corresponding to the exposure parameters when collecting palm print feature data.

[0192] If the exposure parameters of the color camera match the default exposure parameters, and the terminal device detects an object moving toward the color camera and moving to a distance less than a set distance threshold, then the terminal device can take the object as the target object and capture the current facial image of the target object through the color camera to extract the current facial feature data of the target object from the current facial image.

[0193] In step S1403, the terminal device searches for historical facial feature data that matches the current facial feature data of the target object from the historical device parameter set.

[0194] Optionally, the terminal device locally stores a historical device parameter set. This set includes historical exposure parameters of the color camera deployed on the terminal device, historical exposure parameters of the infrared camera, and mapping relationships between historical facial feature data. The facial feature data of the object refers to the facial feature data of the object collected during historical identity recognition processes under successful recognition conditions. In other words, see [link to relevant documentation]. Figure 15 As shown, the historical facial feature data included in the historical device parameter set consists of facial feature data of historical objects whose identity information was successfully identified; the historical exposure parameters of the color camera refer to the exposure parameters of the color camera when the object's identity was successfully identified, and the historical exposure parameters of the infrared camera refer to the exposure parameters of the infrared camera when the object's identity was successfully identified. See also... Figure 16 As shown, the historical exposure parameters of the infrared camera include the exposure time of the infrared camera, the gain parameters of the image signal processing unit, the gain parameters of the photosensitive chip, the focal length, and the current of the infrared lamp when identity recognition is successful; the historical exposure parameters of the color camera include the exposure time of the color camera, the gain parameters of the image signal processing unit, the gain parameters of the photosensitive chip, and the focal length when identity recognition is successful.

[0195] Therefore, historical facial feature data that matches the current facial feature data of the target object can be found from the historical device parameter set.

[0196] Optionally, the historical device parameter set includes a historical facial feature dataset and a historical exposure parameter set. The historical facial feature dataset contains historical facial feature data, and the historical exposure parameter set contains historical exposure parameters of the color camera and the infrared camera. There is a correlation between the historical facial feature data in the historical facial feature dataset and the historical exposure parameters of the color camera and the infrared camera in the historical exposure parameter set. You can first search for historical facial feature data that matches the current facial feature data of the target object in the historical facial feature dataset. If a match is found, then retrieve the historical exposure parameters of the color camera and the infrared camera corresponding to the searched historical facial feature data from the historical exposure parameter set.

[0197] Step S1404: If no historical facial feature data matching the current facial feature data of the target object is found in the historical device parameter set, the exposure parameters of the color camera and the infrared camera are adjusted according to the automatic exposure strategy.

[0198] If no historical facial feature data matching the current facial feature data of the target object is found in the historical device parameter set, it indicates that the target object's palm print image and palm vein infrared image were not captured by the terminal device's infrared camera and color camera before, or even if the target object's palm print image and palm vein infrared image were captured, the target object's identity information was not successfully identified based on the captured images. Therefore, the exposure parameters of the color camera and infrared camera can be adjusted separately according to the automatic exposure strategy, where the automatic exposure strategy is a strategy that automatically adjusts the exposure parameters of the color camera and infrared camera according to the intensity of light.

[0199] Step S1405: If no historical facial feature data matching the current facial feature data of the target object is found in the historical device parameter set, then the historical exposure parameters of the infrared camera and the historical exposure parameters of the color camera corresponding to the found historical facial feature data are obtained from the historical device parameter set.

[0200] If historical facial feature data matching the current facial feature data of the target object is found from the historical device parameter set, it indicates that the target object's identity information was successfully identified by the palm print image and palm vein infrared image collected by the infrared camera and color camera of the terminal device before this. Therefore, the historical exposure parameters of the infrared camera and the color camera corresponding to the historical facial feature data found can be obtained from the historical device parameters. In other words, the obtained historical exposure parameters of the infrared camera are the exposure parameters of the infrared camera when the target object's identity information was successfully identified during the historical identity recognition process, and the obtained historical exposure parameters of the color camera are the exposure parameters of the color camera when the target object's identity information was successfully identified during the historical identity recognition process.

[0201] In step S1406, the terminal device adjusts the exposure parameters of the infrared camera based on the historical exposure parameters of the infrared camera, and adjusts the exposure parameters of the color camera based on the historical exposure parameters of the color camera.

[0202] After adjustment, the exposure parameters of the infrared camera are matched with the historical exposure parameters of the infrared camera, and the exposure parameters of the color camera are matched with the historical exposure parameters of the color camera.

[0203] In step S1407, the terminal device acquires the palm print image of the target object through the adjusted color camera and the palm vein infrared image of the target object through the adjusted infrared camera.

[0204] After adjusting the color camera and infrared camera respectively, the color camera captures the palm print image of the target object, and the infrared camera captures the palm vein infrared image of the target object.

[0205] In step S1408, the terminal device transmits the palm print image and palm vein infrared image of the target object to the server.

[0206] After acquiring the palm print image and palm vein infrared image of the target object, the terminal device can send them to the server for processing.

[0207] In step S1409, the server extracts the palm print feature data of the target object from the palm print image of the target object, extracts the palm vein feature data of the target object from the palm vein infrared image of the target object, and fuses the palm print feature data and palm vein feature data of the target object to obtain the palm feature data of the target object.

[0208] After receiving the palmprint image and palm vein infrared image of the target object, the server extracts the palmprint feature data from the palmprint image and the palm vein feature from the palm vein infrared image. The server then fuses the palmprint feature and palm vein feature to obtain the palm feature of the target object.

[0209] In step S1410, the server identifies the target object's identity information based on the target object's palm feature data and transmits the target object's identity information to the terminal device.

[0210] The server contains a set of identity information, which includes the identity information of different objects and their corresponding palm feature data. The server can retrieve the identity information corresponding to the palm feature data of the target object from the identity information set, use the retrieved identity information as the identity information of the target object, and send it to the terminal device.

[0211] In other words, see Figure 17 As shown, the terminal device includes a historical facial feature dataset and a historical exposure parameter set. The terminal device first searches for historical facial feature data that matches the current facial feature data of the target object from the historical facial feature dataset. Then, it obtains the historical exposure parameters that match the historical facial feature data from the historical device parameter set. Based on the obtained historical exposure parameters, it adjusts the exposure parameters of the infrared camera and the color camera, and acquires palm vein infrared images through the infrared camera and palmprint images through the color camera. The palmprint images and palm vein infrared images are then transmitted to the server. The server performs identity recognition based on the palmprint images and palm vein infrared images and transmits the recognized identity information to the terminal device.

[0212] In step S1411, the terminal device acquires the exposure parameters of the color camera and the infrared camera, and associates and stores the acquired exposure parameters and the current facial feature data of the target object into the historical device parameter set.

[0213] After receiving the target object's identity information from the server, the terminal device indicates successful identification of the target object. Therefore, it can acquire the exposure parameters of the color camera and infrared camera, and associate these parameters with the target object's current facial feature data. Then, it stores the associated color camera exposure parameters, infrared camera exposure parameters, and the target object's current facial feature data in a historical device parameter set. For example, see [link to relevant documentation]. Figure 18 As shown, the exposure parameters of the color camera and the infrared camera are associated with facial feature data under the condition of successful identity recognition, and then stored.

[0214] Optionally, the obtained exposure parameters, the received target object identification information, and the target object's current facial feature data can be associated and stored in the historical device parameter set.

[0215] Optionally, after receiving the identity information of the target object sent by the server, the terminal device can also obtain the successful recognition time of the target object's identity recognition, and calculate the time difference between the acquisition time of the target object's current facial feature data (or current facial image) and the successful recognition time. If the time difference is less than the set time difference threshold, the acquired exposure parameters and the target object's current facial feature data are then associated and stored in the historical device parameter set.

[0216] In step S1412, the terminal device increases the field of view of the color camera according to the default exposure parameters, thereby capturing the facial image of the next object to be identified through the camera with the increased field of view.

[0217] It should be noted that the specific implementation details of steps S1401-S1412 have been described in detail in the foregoing embodiments, and will not be repeated here.

[0218] Figure 14 In the illustrated embodiment, the current exposure parameters of the infrared and color cameras are adjusted by using the historical exposure parameters of the infrared and color cameras under the condition that the target object has been successfully identified in the past. This makes the adjusted exposure parameters match the user's habits. Based on the image of the target object captured by the adjusted infrared and color cameras, identity recognition can be performed, which can improve the success rate and accuracy of identity recognition.

[0219] See Figure 19 , Figure 19 This is a block diagram illustrating an identity recognition device as shown in an exemplary embodiment of this application. Figure 19 As shown, the device includes:

[0220] The acquisition module 1901 is configured to acquire the historical device parameters corresponding to the target object to be identified; wherein, the historical device parameters are the device parameters used to collect identity recognition information during the historical identity recognition process of the target object;

[0221] Adjustment module 1902 is configured to adjust the device parameters of the current acquisition device based on historical device parameters;

[0222] The acquisition module 1903 is configured to acquire the identity information of the target object through the current acquisition device after the device parameters are adjusted.

[0223] The identification module 1904 is configured to identify the target object based on the identification information collected by the current acquisition device.

[0224] In an optional embodiment, based on the foregoing example, the acquisition module 1901 is specifically configured as follows: if a target object to be identified is detected, the current identification information of the target object is acquired; historical identification information matching the current identification information is searched from the historical device parameter set; wherein, the historical device parameter set contains the mapping relationship between historical identification information and historical device parameters of different objects; and the historical device parameters corresponding to the searched historical identification information are acquired.

[0225] In an optional embodiment, based on the foregoing example, the device further includes a storage module configured to: acquire historical identification information of the target object during the historical identification process of the target object, and acquire identification information through a historical acquisition device; acquire device parameters of the historical acquisition device used to acquire identification information, and associate and store the historical identification information of the target object and the acquired device parameters in a historical device parameter set.

[0226] In an optional embodiment, based on the foregoing example, the storage module is further configured to: identify the target object based on the identification information collected by the historical acquisition device; if the identity information of the target object is successfully identified based on the identification information collected by the historical acquisition device, then obtain the device parameters of the historical acquisition device when collecting the identification information, and associate and store the historical identification information of the target object and the obtained device parameters of the historical acquisition device in the historical device parameter set.

[0227] In an optional embodiment, based on the foregoing example, the storage module is further configured to: if the identity information corresponding to the identity information collected by the historical acquisition device is successfully identified, then obtain the successful identification time; calculate the time difference between the acquisition time of the historical identification information of the target object and the successful identification time; if the time difference is less than a set time difference threshold, then use the successfully identified identity information as the identity information of the target object, and obtain the device parameters when the historical acquisition device collected the identity information.

[0228] In an optional embodiment, based on the foregoing example, the storage module is further configured to: associate and store the historical identification information of the target object, the device parameters of the historical acquisition device, and the identity information of the target object successfully identified based on the identity recognition information acquired by the historical acquisition device into the historical device parameter set.

[0229] In an optional embodiment, based on the foregoing example, under the condition that the historical device parameter set contains the mapping relationship between historical identification information of different objects, historical device parameters and identity information, the identification module 1904 is specifically configured as follows: searching for the target identity information corresponding to the current identification information from the historical device parameter set; searching for the identity recognition information corresponding to the target identity information from the identity information set, and comparing the found identity recognition information with the identity recognition information collected by the current collection device; if the found identity recognition information matches the identity recognition information collected by the current collection device, then the target identity information is used as the identity information of the target object.

[0230] In an optional embodiment, based on the foregoing example, the acquisition module 1901 is further configured to: if a target object to be identified is detected, collect the current identification information of the target object through the current acquisition device; wherein the current identification information is of a different type than the identity recognition information.

[0231] In an optional embodiment, based on the foregoing example, if the current acquisition device includes a camera, the adjustment module 1902 is further configured to: increase the field of view of the camera according to the set default device parameters, so as to acquire the identification information of the next object to be identified according to the camera with the increased field of view.

[0232] In an optional embodiment, based on the foregoing example, the identification module 1904 is further configured to: if the identity information of the target object is not identified based on the identity information collected by the current acquisition device within a specified time period, then the device parameters of the current acquisition device are readjusted according to the set adjustment strategy; the current acquisition device with readjusted device parameters re-acquires the identity information of the target object; and the target object is identified based on the re-acquired identity information.

[0233] In an optional embodiment, based on the foregoing example, under the condition that the current acquisition device includes a color camera and an infrared camera, the acquisition module 1903 is specifically configured as follows: acquiring palm print feature data of the target object through the color camera with adjusted device parameters, and acquiring palm vein feature data of the target object through the infrared camera with adjusted device parameters; fusing the palm print feature data and the palm vein feature data to obtain the palm feature data of the target object, and using the palm feature data as the identity recognition information of the target object acquired by the current acquisition device.

[0234] It should be noted that the identity recognition device provided in the above embodiments and the identity recognition method provided in the above embodiments belong to the same concept. The specific way in which each module and unit performs operations has been described in detail in the method embodiments, and will not be repeated here.

[0235] It should be noted that, in this application, the technology for identity recognition based on biometric information and identity card information, when applied to specific products or technologies according to the above embodiments of this application, ensures that the relevant data collection, use and processing processes comply with national laws and regulations. Before collecting biometric information and identity card information, the information processing rules have been communicated and the individual consent of the target object has been obtained. Biometric information and identity card information are processed in strict accordance with legal requirements and personal information processing rules, and technical measures are taken to ensure the security of relevant data.

[0236] Embodiments of this application also provide an electronic device, including: one or more processors; and a storage device for storing one or more computer programs, which, when executed by one or more processors, cause the electronic device to implement the identity recognition methods provided in the above embodiments.

[0237] Figure 20 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown.

[0238] It should be noted that, Figure 20 The computer system 2000 of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0239] like Figure 20 As shown, the computer system 2000 includes a Central Processing Unit (CPU) 2001, which can perform various appropriate actions and processes based on a computer program stored in Read-Only Memory (ROM) 2002 or a computer program loaded from Storage Unit 2008 into Random Access Memory (RAM) 2003, such as executing the identification method described in the above embodiments. The RAM 2003 also stores various computer programs and data required for system operation. The CPU 2001, ROM 2002, and RAM 2003 are interconnected via a bus 2004. An Input / Output (I / O) interface 2003 is also connected to the bus 2004.

[0240] In some embodiments, the following components are connected to the I / O interface 2003: an input section 2006 including a keyboard, mouse, etc.; an output section 2007 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 2008 including a hard disk, etc.; and a communication section 2009 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 2009 performs communication processing via a network such as the Internet. A drive 2010 is also connected to the I / O interface 2003 as needed. A removable medium 2011, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 2010 as needed so that computer programs read from it can be installed into the storage section 2008 as needed.

[0241] In particular, according to embodiments of this application, a computer program implementing the identity recognition method can be carried on a computer-readable medium, which can be downloaded and installed from a network via the communication section 2009, and / or installed from a removable medium 2011.

[0242] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a computer program that can be used by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer program contained in the computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0243] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and a computer program.

[0244] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0245] Another aspect of this application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor of an electronic device, enables the electronic device to implement the aforementioned identification method. This computer-readable storage medium may be included in the electronic device described in the above embodiments, or it may exist independently and not assembled into the electronic device.

[0246] Another aspect of this application provides a computer program product comprising a computer program that, when executed by a processor, implements the identity recognition methods provided in the various embodiments described above. The computer program may be stored in a computer-readable storage medium.

[0247] The above description is merely a preferred exemplary embodiment of this application and is not intended to limit the implementation of this application. Those skilled in the art can easily make corresponding modifications or alterations based on the main concept and spirit of this application. Therefore, the scope of protection of this application should be determined by the scope of protection claimed in the claims.

Claims

1. An identity recognition method, characterized in that, The method includes: Obtain the historical device parameters corresponding to the target object to be identified; wherein, the historical device parameters are the device parameters used to collect identity recognition information during the historical identity recognition process of the target object; Adjust the current data acquisition device parameters based on the historical device parameters; The current acquisition device, after adjusting its parameters, acquires the identity information of the target object. The target object is identified based on the identity information collected by the current acquisition device. The process of obtaining the historical device parameters corresponding to the target object to be identified includes: If a target object to be identified is detected, the current identification information of the target object is obtained; wherein, the current identification information is of a different type than the identity recognition information; Search for historical identification information that matches the current identification information from the historical device parameter set; wherein, the historical device parameter set contains the mapping relationship between historical identification information and historical device parameters of different objects; Retrieve the historical device parameters corresponding to the found historical identifier information.

2. The method as described in claim 1, characterized in that, Before searching for historical identification information that matches the current identification information from the historical device parameter set, the method further includes: During the historical identity recognition process of the target object, the historical identification information of the target object is obtained, and the identity recognition information is collected through the historical acquisition device; Obtain the device parameters of the historical acquisition device used to collect identity recognition information, and associate and store the historical identification information of the target object and the acquired device parameters in the historical device parameter set.

3. The method as described in claim 2, characterized in that, The step of acquiring the device parameters used by the historical data acquisition device to collect identity information, and associating and storing the historical identification information of the target object and the acquired device parameters in the historical device parameter set, includes: The target object is identified based on the identity information collected by the historical data acquisition device. If the identity information of the target object is successfully identified based on the identity recognition information collected by the historical acquisition device, then the device parameters of the historical acquisition device when collecting the identity recognition information are obtained, and the historical identification information of the target object and the obtained device parameters of the historical acquisition device are associated and stored in the historical device parameter set.

4. The method as described in claim 3, characterized in that, If the identity information of the target object is successfully identified based on the identity recognition information collected by the historical acquisition device, then the device parameters of the historical acquisition device when collecting the identity recognition information are obtained, including: If the identity information corresponding to the identity information collected by the historical data collection device is successfully identified, the successful identification time is obtained; Calculate the time difference between the acquisition time of the historical identification information of the target object and the successful identification time; If the time difference is less than the set time difference threshold, the successfully identified identity information will be used as the identity information of the target object, and the device parameters of the historical acquisition device when collecting identity recognition information will be obtained.

5. The method as described in claim 3, characterized in that, The step of associating and storing the historical identification information of the target object and the acquired device parameters of the historical acquisition device in the historical device parameter set includes: The historical identification information of the target object, the device parameters of the historical acquisition device, and the identity information of the target object successfully identified based on the identity recognition information collected by the historical acquisition device are associated and stored in the historical device parameter set.

6. The method as described in claim 1, characterized in that, The historical device parameter set contains the mapping relationship between historical identification information, historical device parameters, and identity information of different objects; The step of identifying the target object based on the identity information collected by the current acquisition device includes: Search the target identity information corresponding to the current identification information from the historical device parameter set; The system retrieves the identity information corresponding to the target identity information from the identity information set and compares the retrieved identity information with the identity information collected by the current acquisition device. If the found identity information matches the identity information collected by the current collection device, then the target identity information is used as the identity information of the target object.

7. The method as described in claim 1, characterized in that, If a target object to be identified is detected, the current identification information of the target object is obtained, including: If a target object to be identified is detected, the current identification information of the target object is collected through the current acquisition device.

8. The method as described in claim 7, characterized in that, The current acquisition device includes a camera; after identifying the target object based on the identity information acquired by the current acquisition device, the method further includes: The field of view of the camera is increased according to the default device parameters, so as to collect the identification information of the next object to be identified based on the increased field of view of the camera.

9. The method as described in claim 1, characterized in that, The method further includes: If the identity information of the target object is not identified based on the identity recognition information collected by the current acquisition device within a specified time period, the device parameters of the current acquisition device shall be readjusted according to the set adjustment strategy. The current acquisition device, after readjusting its parameters, re-acquires the identity information of the target object; The target object is identified based on the re-collected identity information.

10. The method as described in claim 1, characterized in that, The current data acquisition device includes a color camera and an infrared camera; The acquisition of the target object's identity information by the current acquisition device after adjusting the device parameters includes: The palm print feature data of the target object is collected by a color camera with adjusted device parameters, and the palm vein feature data of the target object is collected by an infrared camera with adjusted device parameters. The palm print feature data and the palm vein feature data are fused to obtain the palm feature data of the target object, and the palm feature data is used as the identity recognition information of the target object collected by the current acquisition device.

11. An identity recognition device, characterized in that, The device includes: The acquisition module is configured to acquire historical device parameters corresponding to the target object to be identified; wherein, the historical device parameters are the device parameters used to collect identity recognition information during the historical identity recognition process of the target object; The adjustment module is configured to adjust the device parameters of the current acquisition device based on the historical device parameters. The acquisition module is configured to acquire the identity information of the target object through the current acquisition device after adjusting the device parameters; The identification module is configured to identify the target object based on the identification information collected by the current acquisition device. The process of obtaining the historical device parameters corresponding to the target object to be identified includes: If a target object to be identified is detected, the current identification information of the target object is obtained; wherein, the current identification information is of a different type than the identity recognition information; Search for historical identification information that matches the current identification information from the historical device parameter set; wherein, the historical device parameter set contains the mapping relationship between historical identification information and historical device parameters of different objects; Retrieve the historical device parameters corresponding to the found historical identifier information.

12. An electronic device, characterized in that, include: One or more processors; A storage device for storing one or more computer programs that, when executed by one or more processors, cause the electronic device to implement the identification method according to any one of claims 1-10.

13. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by the processor of the electronic device, causes the electronic device to implement the identity recognition method according to any one of claims 1-10.

14. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the identity recognition method according to any one of claims 1-10.

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