WO2020093634A1

WO2020093634A1 - Face recognition-based method, device and terminal for adding image, and storage medium

Info

Publication number: WO2020093634A1
Application number: PCT/CN2019/077220
Authority: WO
Inventors: 戴磊
Original assignee: 平安科技（深圳）有限公司
Priority date: 2018-11-06
Filing date: 2019-03-06
Publication date: 2020-05-14
Also published as: CN109598203A

Abstract

A face recognition-based method, device and terminal device for adding an image and a storage medium. The method comprises: acquiring the degree of similarity between a first snapshot image and a sample library image (101); determining whether the degree of similarity is within a preset degree of similarity threshold (102); if the determination result is yes, automatically adding the first snapshot image to the sample library (103); and carrying out face authentication and acquiring a face authentication result (104). By means of the described method, the recognition functions of an entire face recognition system may be improved.

Description

Photo adding method, device, terminal and storage medium based on face recognition

This application requires the priority of the Chinese patent application submitted to the China Patent Office on November 6, 2018 with the application number 201811315455.7 and the invention titled "Photo-adding method, device, terminal and storage medium based on face recognition" Incorporated by reference in this application.

Technical field

The present application relates to the field of biometrics technology, and in particular, to a method for adding photos based on face recognition, a device for adding photos based on face recognition, a terminal device, and a storage medium.

Background technique

This section is intended to provide background or context for the implementation of the embodiments of the present application set forth in the claims and specific implementations. The description here is not admitted to be prior art because it is included in this section.

The traditional face recognition technology is based on the facial features of the person. For the input face image or video stream: first determine whether there is a face, if there is a face, then further give the position, size and The location information of each major facial organ. Based on this information, the identity features contained in each face are further extracted and compared with known faces to identify the identity of each face.

The traditional face recognition technology compares the recognized face with the known face saved by the system, but due to the limitations of the face saved by the system, such as the bangs, fat and thin, and makeup of the recognized face The saved faces are different, so there is a risk that the faces will not be recognized, and I need to find relevant personnel again to take the latest photos.

Summary of the invention

In view of this, it is necessary to provide a photo addition method based on face recognition, a photo addition device based on face recognition, a terminal device, and a storage medium, which can enhance the recognition capability of the entire face recognition system.

An aspect of an embodiment of the present application provides a method for adding photos based on face recognition. The method includes:

Get the similarity between the first snapshot and the photos in the sample library;

Determine whether the similarity is within a preset similarity threshold;

If the similarity is within the preset similarity threshold, the first captured photo is automatically added to the sample library;

Perform face authentication, and obtain the face authentication result.

Another aspect of the embodiments of the present application further provides a photo adding device based on face recognition, the device includes:

The similarity obtaining module is used to obtain the similarity between the first captured photo and the photos in the sample library;

The judgment module is used to judge whether the similarity is within a preset similarity threshold;

A photo adding module, configured to automatically add the first captured photo to the sample library when the judgment module determines that the similarity is within the preset similarity threshold;

The face authentication module is used to perform face authentication and obtain the face authentication result.

In yet another aspect, embodiments of the present application further provide a terminal device, the terminal device includes a processor, and the processor is configured to implement any one of the above-described face recognition-based Steps to add photos.

According to still another aspect of the embodiments of the present application, a non-volatile readable storage medium is provided. The non-volatile readable storage medium stores computer-readable instructions, which are implemented when executed by a processor. The steps of the photo adding method based on face recognition described in any one of the above.

Embodiments of the present application provide a method for adding photos based on face recognition, a device for adding photos based on face recognition, a terminal device, and a storage medium to obtain the similarity between a first captured photo and a sample library photo; and determine whether the similarity is Within a preset similarity threshold; if the similarity is within the preset similarity threshold, automatically add the first captured photo to the sample library; perform face authentication, and obtain the face authentication result. Using the embodiment of the present application, for the newly captured photos, whether the similarity with the pre-set sample library photos reaches the preset similarity threshold, or the similarity with the captured photos automatically added to the sample library reaches the preset similarity threshold , All believe that face authentication is successful, which can enhance the recognition ability of the entire face recognition system.

BRIEF DESCRIPTION

FIG. 1 is a flowchart of a method for adding photos based on face recognition provided by an embodiment of the present application.

2 is a schematic structural diagram of a terminal device according to an embodiment of the present application.

FIG. 3 is an exemplary functional block diagram of the terminal device shown in FIG. 2.

detailed description

In order to understand the above-mentioned objects, features and advantages of the embodiments of the present application more clearly, the present application will be described in detail below with reference to the drawings and specific implementations. It should be noted that, in the case of no conflict, the features in the embodiments of the present application may be combined with each other.

In the following description, many specific details are set forth in order to fully understand the embodiments of the present application. The described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the embodiments of the present application.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field that belong to the embodiments of the present application. The terminology used in the specification of the present application herein is only for the purpose of describing specific embodiments, and is not intended to limit the embodiments of the present application.

FIG. 1 is a flowchart of a method for adding photos based on face recognition provided by an embodiment of the present application. The method for adding photos based on face recognition can be applied to an intelligent terminal equipped with a camera and / or a scanner. The terminal may be a smart watch, a smart phone, a tablet computer, a personal digital assistant (Personal Digital Assistant, PDA) and other smart devices. The terminal may perform data interaction with the server through a wireless network (for example, Bluetooth, WIFI, infrared, etc.). As shown in FIG. 1, the method for adding photos based on face recognition may include the following steps:

S101: Obtain the similarity between the first captured photo and the photos in the sample library.

In this embodiment, the camera that performs face recognition may use a high-definition camera, for example, a camera with no less than 10 million pixels. The similarity may be calculated based on the characteristics of the first captured photo and the characteristics of the sample library photo. Specifically, the method for obtaining the similarity between the first captured photo and the sample library photo includes: performing face detection on the collected video image to obtain the first captured photo; and collecting the user's face in the first captured photo Information to obtain the user ’s face image; obtain the preset area of the user ’s face image and calculate the image characteristics of the preset area; compare the image characteristics of the preset area of the first captured photo with those of the sample library photos The similarity of the image features of the preset area. The similarity of the image features of the two preset regions can be measured as the similarity by calculating the distance between the image features. For example, the cos distance or the Euclidean distance between the preset region features of two face images can be calculated to measure a Similarity corresponding to facial image features. The similarity between the image feature of the preset area of the first captured photo and the image feature of the preset area of the sample library photo is the similarity of the first captured photo and the sample library photo. The preset area may include one or more of areas such as human eyes, nose, mouth, and edges of human faces.

The method for performing face detection may include one or more of a detection algorithm based on face feature points, a detection algorithm based on an entire face image, a detection algorithm based on a template, and an algorithm using neural network for detection, The information detected by the face may include facial feature information, facial curve information, and the like. Taking the recognition algorithm based on neural network as an example, the method of performing face detection on the collected video images includes: collecting a large number of face samples in advance, and training to obtain a deep convolutional neural network for face detection; then the Video image data is input to the face detection deep convolutional neural network to obtain a face feature map, and an area on the face feature map whose overall score exceeds a set threshold is regarded as a face area. The set threshold may be a value obtained by a person skilled in the art based on experience.

It can be understood that, before the preset area of the user's face image is acquired, the first snapshot photos and the sample library photos may be classified and labeled, and the first snapshot photos and the Perform face alignment operations on the photos in the sample library. The face alignment operation may include performing operations such as rotating, zooming in, zooming out, or cutting on the photos in the sample library. The face alignment operation can ensure that stable features are extracted and a better face recognition effect is obtained, so as to remove the influence of face angle on face recognition.

S102: Determine whether the similarity is within a preset similarity threshold. If the judgment result is yes, proceed to step S103.

In this embodiment, the method for determining whether the similarity is within a preset similarity threshold may include: separately calculating the image characteristics of each preset area of the first captured photo and each pre-calculation of the sample library photos Let the average similarity of the image features of the area (ie, calculate the average of the similarity of the image features of each preset area of the first captured photo and the image features of each preset area of the sample library photo, Specifically, the similarity between the image feature of each preset area of the first captured photo and the image feature of each preset area of the sample library photo may be calculated first, and then the image feature of each preset area The average value of the similarity of. The method for calculating the average similarity is not limited in this embodiment), where the number of the preset areas is greater than one; it is determined whether the average similarity is within the preset similarity Within the threshold; if it is determined that the average similarity is within the preset similarity threshold, the first captured photo is automatically added to the sample library. Or, calculate the similarity between the image feature of each preset area of the first captured photo and the image feature of each preset area of the sample library photo; determine whether the similarity is all within the preset similarity threshold If the judgment result is yes, the first snapshot is automatically added to the sample library.

The preset similarity threshold may be flexibly set according to a specific application scenario. For example, a face image feature progress simulation corresponding to multiple photos may be simulated, and finally a threshold is determined as the similarity threshold. According to the first method, that is, to determine whether the average similarity between the image feature of the preset area of the first captured photo and the image feature of the preset area of the sample library photo is within a preset similarity threshold, it is commonly used, The preset similarity threshold may be a percentage value above 90%, for example, 90% or 92%. According to the second method, that is, whether the similarity between the image feature of each preset area of the first captured photo and the image feature of each preset area of the sample library photo is within the preset similarity threshold , Then the number of the preset similarity thresholds is consistent with the number of the preset areas (the number is at least 2), the image features of each preset area of the first captured photo and each of the photos of the sample library The threshold of the similarity of image features of a preset area may be the same. Of course, it can also be set to be different according to the feature distribution. For example, for the preset area being the outer edge of the face, the preset similarity threshold may be smaller, while for the area such as human eye position and human nose position, The preset similarity threshold may be set relatively large.

S103: Automatically add the first captured photo to the sample library.

In this embodiment, before the first captured photo is automatically added to the sample library, the method further includes: outputting a prompt, the content of the prompt includes whether to add the first captured photo to the sample library. The method of prompting may include voice prompting, short message prompting, and the like. It can be understood that if the user's prompt is not received within the preset duration (for example, the preset duration is 10 seconds), the system automatically adds the first captured photo to the sample library. By outputting prompts, the staff can consider whether to update the sample library photos according to the actual situation, making the photo addition system based on face recognition more user-friendly.

After automatically adding the first captured photo to the sample library, the method further includes: updating the first captured photo saved in the sample library at a preset time interval; wherein, the updated captured photo The similarity with the sample library photos is not less than the similarity between the first snapshot photos and the sample library photos. It can be understood that a preset time interval is set, and within the preset time interval after the first captured photo is automatically added to the sample library, the sample library does not need to be updated. The sample library may include original photos of the sample library and a preset number of captured photos. The preset time interval and the preset number may be preset by the system, or may be preset by an end user. For example, the preset time interval is 30 days, and the preset number is 2 sheets. Preferably, there is a large gap in the shooting environment of the preset number of captured photos added to the sample library, and the shooting environment may include light brightness, angle of the captured face, and the like. If the time when the captured photos are automatically added to the sample library exceeds a preset time interval, the system automatically updates the captured photos in the sample library during the face recognition process thereafter. The similarity between the snapshot photo used for updating and the original photo in the sample library is not less than the similarity between the snapshot photo (that is, the first snapshot photo) already saved in the sample library and the original photo, and preferably, the There is a large gap between the updated second snapshot photos and the remaining snapshot photos already stored in the sample library.

S104: Perform face authentication, and obtain the face authentication result.

In this embodiment, the face authentication may be 1: N face authentication or 1: 1 face authentication. The face authentication result includes: authentication success and authentication failure. Wherein, the method for successful authentication includes: when the similarity between the second captured photo and the original photo of the sample library reaches a preset similarity threshold, the face authentication result is obtained as authentication successful, wherein, the first The second snapshot is the one captured after the first snapshot is automatically added to the sample library, and then is used for face authentication again; or, the second snapshot and the first snapshot in the sample library The similarity reaches the preset similarity threshold. That is, if the similarity between the second captured photo and any photo stored in the sample library reaches a preset similarity threshold, it is considered that the authentication is successful. It can be understood that the sampling time of the original photos of the sample library may be earlier, and the difference between the shooting environment and the shooting environment of the live photos during face authentication may also be greater. The original photos of the sample library are relative to the first snapshot Photo recognition accuracy may be low. Therefore, in the actual face authentication process, preferably, the similarity between the second captured photo and the first captured photo in the sample library may be compared. If the similarity reaches a preset similarity threshold, it indicates that the authentication is successful.

An embodiment of the present application provides a method for adding photos based on face recognition to obtain the similarity between a first captured photo and a sample library photo; determine whether the similarity is within a preset similarity threshold, and if the judgment result is yes, then Automatically add the first captured photo to the sample library; perform face authentication, and obtain the face authentication result. Using the embodiment of the present application, for the newly captured photos, whether the similarity with the pre-set sample library photos reaches the preset similarity threshold, or the similarity with the captured photos automatically added to the sample library reaches the preset similarity threshold , All believe that face authentication is successful, which can enhance the recognition ability of the entire face recognition system.

The above is a detailed description of the method provided by the embodiments of the present application. According to different requirements, the execution order of the blocks in the flowchart can be changed, and some blocks can be omitted. The terminal provided by the embodiment of the present application will be described below.

An embodiment of the present application further provides a terminal device 1, including a memory 10, a processor 30, and computer-readable instructions stored on the memory 10 and executable on the processor 30, which is implemented when the processor 30 executes the program The steps of the photo adding method based on face recognition described in any of the above embodiments.

2 is a schematic structural diagram of a terminal device according to an embodiment of the present application. As shown in FIG. 2, the terminal device 1 includes a memory 10 in which a photo adding device 100 based on face recognition is stored. The terminal device 1 may be a terminal with an application display function such as a mobile phone, a tablet computer, a personal digital assistant, or the like. The photo adding device 100 based on face recognition can obtain the similarity between the first captured photo and the sample library photo; determine whether the similarity is within a preset similarity threshold, and if the judgment result is yes, then add the first A snapshot is automatically added to the sample library; face authentication is performed, and the face authentication result is obtained. Using the embodiment of the present application, for the newly captured photos, whether the similarity with the preset sample library photos reaches the preset similarity threshold, or the similarity with the captured photos automatically added to the sample library reaches the preset similarity threshold , All believe that face authentication is successful, which can enhance the recognition ability of the entire face recognition system.

In this embodiment, the terminal device 1 may be a mobile phone. The terminal device 1 may further include a display screen 20 and a processor 30. The memory 10 and the display screen 20 may be electrically connected to the processor 30 respectively.

The memory 10 may be different types of storage devices for storing various types of data. For example, it may be the memory and internal memory of the terminal device 1, or a memory card that can be externally connected to the terminal device 1, such as flash memory, SM card (Smart Media Card, smart media card), SD card (Secure Digital Card, secure digital Card) etc. In addition, the memory 10 may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart, Media, Card, SMC), and a secure digital (SD) Card, flash memory card (Flash), at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device. The memory 10 is used to store various types of data, for example, various types of applications (Applications) installed in the terminal device 1, data set and acquired by applying the above-described photo addition method based on face recognition, and other information.

The display screen 20 is installed in the terminal device 1 and used for displaying information.

The processor 30 is used to execute the method for adding photos based on face recognition and various types of software installed in the terminal device 1, such as an operating system and application display software. The processor 30 includes but is not limited to a processor (Central Processing Unit, CPU), a micro controller unit (Micro Controller Unit, MCU), and other devices for interpreting computer instructions and processing data in computer software.

The photo adding device 100 based on face recognition may include one or more modules, which are stored in the memory 10 of the terminal device 1 and configured to be configured by one or more processors ( This embodiment is executed by one processor 30) to complete the embodiment of the present application. For example, referring to FIG. 3, the photo adding device 100 based on face recognition may include a similarity acquiring module 101, a determining module 102, a photo adding module 103, and a face authentication module 104. The module referred to in the embodiment of the present application may be a program segment that performs a specific function, and is more suitable than a program for describing the execution process of software in a processor.

It can be understood that, corresponding to the above embodiments in the photo adding method based on face recognition, the terminal device 1 may include some or all of the functional modules shown in FIG. 3, and the functions of each module will be specifically described below . It should be noted that the same noun-related nouns and specific explanations in the above embodiments of the method for adding photos based on face recognition can also be applied to the following function introduction to each module. To save space and avoid duplication, I will not repeat them here.

The similarity obtaining module 101 can be used to obtain the similarity between the first captured photo and the sample library photo.

The judgment module 102 may be used to judge whether the similarity is within a preset similarity threshold.

The photo adding module 103 may be used to automatically add the first captured photo to the sample library when the judgment module determines that the similarity is within the preset similarity threshold.

The face authentication module 104 can be used to perform face authentication and obtain the face authentication result.

Embodiments of the present application also provide a non-volatile readable storage medium on which computer-readable instructions are stored, and when the computer-readable instructions are executed by a processor, the face recognition-based Steps to add photos.

If the photo-adding device 100 / terminal device 1 / computer device integrated module / unit based on face recognition is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a non-volatile Read the storage medium. Based on this understanding, the present application can implement all or part of the processes in the methods of the above embodiments, or it can be completed by instructing relevant hardware through computer-readable instructions, which can be stored in a non-volatile When reading the storage medium, the computer-readable instructions, when executed by the processor, can implement the steps of the foregoing method embodiments. Wherein, the computer readable instructions include computer readable instruction codes, and the computer readable instruction codes may be in source code form, object code form, executable file, or some intermediate form, etc. The non-volatile readable storage medium may include: any entity or device capable of carrying the computer-readable instruction code, a recording medium, a U disk, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM , Read-Only Memory), Random Access Memory (RAM, Random Access Memory), electrical carrier signals, telecommunications signals, and software distribution media.

The so-called processor 30 may be a central processing unit (Central Processing Unit, CPU), or other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application-specific integrated circuits (Application Specific Integrated Circuit, ASIC), Ready-made programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The processor 30 is the control center of the photo recognition device 100 / terminal device 1 based on face recognition, using various The interface and the line connect the various parts of the entire photo adding device 100 / terminal device 1 based on face recognition.

The memory 10 is used to store the computer-readable instructions and / or modules, and the processor 30 executes or executes the computer-readable instructions and / or modules stored in the memory 10, and the calls are stored in the memory 10 The data inside realizes various functions of the photo adding device 100 / terminal device 1 based on face recognition. The memory 10 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, application programs required by at least one function (such as a sound playback function, an image playback function, etc.), etc .; Store data (such as audio data, phone book, etc.) created according to the use of mobile phones. In addition, the memory 10 may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart, Media, Card, SMC), and a secure digital (SD) Card, flash memory card (Flash), at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device.

In the several specific embodiments provided in this application, it should be understood that the disclosed terminal and method may be implemented in other ways. For example, the system implementation described above is only schematic. For example, the division of the module is only a division of logical functions, and there may be other divisions in actual implementation.

It is obvious to a person skilled in the art that the embodiments of the present application are not limited to the details of the above exemplary embodiments, and can be implemented in other specific forms without departing from the spirit or basic characteristics of the embodiments of the present application example. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-limiting, the scope of the embodiments of the present application is defined by the appended claims rather than the above description, so it is intended to be All changes within the meaning and scope of equivalent requirements of the claims are included in the embodiments of the present application. Any reference signs in the claims should not be considered as limiting the claims involved. Multiple units, modules or devices stated in the system, device or terminal claims may also be implemented by the same unit, module or device through software or hardware.

The above embodiments are only used to illustrate the technical solutions of the embodiments of the present application but not to limit them. Although the embodiments of the present application are described in detail with reference to the above preferred embodiments, those of ordinary skill in the art should understand that Modifications or equivalent replacements of the solutions shall not depart from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

A method for adding photos based on face recognition, characterized in that the method includes:

Get the similarity between the first snapshot and the photos in the sample library;

Determine whether the similarity is within a preset similarity threshold;

If the similarity is within the preset similarity threshold, the first captured photo is automatically added to the sample library;

Perform face authentication, and obtain the face authentication result.
The method for adding photos based on face recognition according to claim 1, wherein the acquiring the similarity between the first captured photo and the sample library photo includes:

Performing face detection on the collected video image to obtain the first captured photo;

Detecting the user's face information in the first captured photo to obtain the user's face image;

Acquiring a preset area of the user's face image, and calculating image characteristics of the preset area;

Comparing the similarity between the image features of the preset area of the first captured photo and the image features of the preset area of the sample library photo.
The method for adding photos based on face recognition according to claim 2, wherein the determining whether the similarity is within a preset similarity threshold includes:

Calculating the average similarity between the image features of each preset area of the first captured photo and the image features of each preset area of the sample library photo, wherein the number of the preset areas is greater than one;

Determine whether the average similarity is within a preset similarity threshold;

If it is determined that the average similarity is within the preset similarity threshold, the first captured photo is automatically added to the sample library.
The method for adding photos based on face recognition according to claim 2, wherein the determining whether the similarity is within a preset similarity threshold includes:

Calculating the similarity between the image feature of each preset area of the first captured photo and the image feature of each preset area of the sample library photo;

Judging whether the similarities are all within the preset similarity threshold;

If the judgment result is yes, the first captured photo is automatically added to the sample library.
The method for adding photos based on face recognition according to claim 3 or 4, wherein before the first captured photo is automatically added to the sample library, the method further comprises:

A prompt is output, and the content of the prompt includes whether to add the first captured photo to the sample library.
The method for adding photos based on face recognition according to claim 1, wherein the obtaining the face authentication result comprises:

When the similarity between the second captured photo and the original photos of the sample library reaches a preset similarity threshold, the face authentication result is obtained as authentication success, wherein the second captured photo is taken on the first captured photo After the photos are automatically added to the sample library, the photos captured during face authentication again; or

When the similarity between the second captured photo and the first captured photo reaches a preset similarity threshold, the face authentication result is obtained as authentication success.
The method for adding photos based on face recognition according to claim 1, wherein after automatically adding the first captured photo to the sample library, the method further comprises:

Updating the first snapshot photos stored in the sample library at preset time intervals; wherein the similarity between the snapshot photos for updating and the sample library photos is not less than the first snapshot photos and the sample library The similarity of the photo.
A photo adding device based on face recognition, characterized in that the device includes:

The similarity obtaining module is used to obtain the similarity between the first captured photo and the photos in the sample library;

The judgment module is used to judge whether the similarity is within a preset similarity threshold;

A photo adding module, configured to automatically add the first captured photo to the sample library when the judgment module determines that the similarity is within the preset similarity threshold;

The face authentication module is used to perform face authentication and obtain the face authentication result.
A terminal device is characterized in that the terminal device includes a processor, and the processor is used to execute the following steps when executing computer-readable instructions stored in a memory:

Get the similarity between the first snapshot and the photos in the sample library;

Determine whether the similarity is within a preset similarity threshold;

If the similarity is within the preset similarity threshold, the first captured photo is automatically added to the sample library;

Perform face authentication, and obtain the face authentication result.
The terminal device according to claim 9, wherein the processor executes the computer-readable instructions to obtain the following steps when acquiring the similarity between the first captured photo and the sample library photo:

Performing face detection on the collected video image to obtain the first captured photo;

Detecting the user's face information in the first captured photo to obtain the user's face image;

Acquiring a preset area of the user's face image, and calculating image characteristics of the preset area;

Comparing the similarity between the image features of the preset area of the first captured photo and the image features of the preset area of the sample library photo.
The terminal device according to claim 10, wherein the processor executes the computer-readable instructions to determine the following steps when determining whether the similarity is within a preset similarity threshold:

Calculating the average similarity between the image features of each preset area of the first captured photo and the image features of each preset area of the sample library photo, wherein the number of the preset areas is greater than one;

Determine whether the average similarity is within a preset similarity threshold;

If it is determined that the average similarity is within the preset similarity threshold, the first captured photo is automatically added to the sample library.
The terminal device according to claim 10, wherein when the processor determines whether the similarity is within a preset similarity threshold, the computer-readable instruction is executed to implement the following steps:

Calculating the similarity between the image feature of each preset area of the first captured photo and the image feature of each preset area of the sample library photo;

Judging whether the similarities are all within the preset similarity threshold;

If the judgment result is yes, the first captured photo is automatically added to the sample library.
The terminal device according to claim 9, wherein the processor executes the computer-readable instructions to obtain the following steps when acquiring the face authentication result:

When the similarity between the second captured photo and the original photos of the sample library reaches a preset similarity threshold, the face authentication result is obtained as authentication success, wherein the second captured photo is taken on the first captured photo After the photos are automatically added to the sample library, the photos captured during face authentication again; or

When the similarity between the second captured photo and the first captured photo reaches a preset similarity threshold, the face authentication result is obtained as authentication success.
The terminal device according to claim 9, wherein after the first captured photo is automatically added to the sample library, the processor executes the computer-readable instructions to implement the following steps:

Updating the first snapshot photos stored in the sample library at preset time intervals; wherein the similarity between the snapshot photos for updating and the sample library photos is not less than the first snapshot photos and the sample library The similarity of the photo.
A non-volatile readable storage medium that stores computer-readable instructions, characterized in that, when the computer-readable instructions are executed by a processor, the following steps are implemented:

Get the similarity between the first snapshot and the photos in the sample library;

Determine whether the similarity is within a preset similarity threshold;

If the similarity is within the preset similarity threshold, the first captured photo is automatically added to the sample library;

Perform face authentication, and obtain the face authentication result.
The storage medium according to claim 15, wherein when acquiring the similarity between the first captured photo and the sample library photo, the computer-readable instructions are executed by the processor to implement the following steps:

Performing face detection on the collected video image to obtain the first captured photo;

Detecting the user's face information in the first captured photo to obtain the user's face image;

Acquiring a preset area of the user's face image, and calculating image characteristics of the preset area;

Comparing the similarity between the image features of the preset area of the first captured photo and the image features of the preset area of the sample library photo.
The storage medium according to claim 16, wherein, when it is determined whether the similarity is within a preset similarity threshold, the computer-readable instructions are executed by the processor to implement the following steps:

Calculating the average similarity between the image features of each preset area of the first captured photo and the image features of each preset area of the sample library photo, wherein the number of the preset areas is greater than one;

Determine whether the average similarity is within a preset similarity threshold;

If it is determined that the average similarity is within the preset similarity threshold, the first captured photo is automatically added to the sample library.
The storage medium according to claim 16, wherein, when it is determined whether the similarity is within a preset similarity threshold, the computer-readable instructions are executed by the processor to implement the following steps:

Calculating the similarity between the image feature of each preset area of the first captured photo and the image feature of each preset area of the sample library photo;

Judging whether the similarities are all within the preset similarity threshold;

If the judgment result is yes, the first captured photo is automatically added to the sample library.
The storage medium according to claim 16, wherein, when acquiring the face authentication result, the computer-readable instructions are executed by the processor to implement the following steps:

When the similarity between the second captured photo and the original photos of the sample library reaches a preset similarity threshold, the face authentication result is obtained as authentication success, wherein the second captured photo is taken on the first captured photo After the photos are automatically added to the sample library, the photos captured during face authentication again; or

When the similarity between the second captured photo and the first captured photo reaches a preset similarity threshold, the face authentication result is obtained as authentication success.
The storage medium according to claim 15, wherein after the first captured photo is automatically added to the sample library, the computer-readable instructions are executed by the processor to implement the following steps:

Updating the first snapshot photos stored in the sample library at preset time intervals; wherein the similarity between the snapshot photos for updating and the sample library photos is not less than the first snapshot photos and the sample library The similarity of the photo.