Living body detection auxiliary method and device for face recognition system

A face recognition system and living body detection technology, applied in the field of living body detection auxiliary methods and devices for face recognition systems, can solve the problems of inability to have very high accuracy, long-term attack, etc., and achieve stable judgment results and increase costs. Effect

Pending Publication Date: 2022-06-03
XIAMEN STAR SMART TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Because the results of single-frame image recognition often cannot have very high accuracy, when the attacker continues to carry out live attacks on the scene for a long time, there is a certain probability that the detection will break through at a certain moment. The longer the time, the higher the probability of breakthrough
[0004] Therefore, it is urgent to propose a new method to solve the risk of long-term attack in view of the attacker's long-time attack

Method used

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  • Living body detection auxiliary method and device for face recognition system

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Comparison scheme
Effect test

Embodiment 1

[0043] like figure 1 As shown, an auxiliary method for living body detection for a face recognition system specifically includes the following steps:

[0044] Step S1: Establish a list of "attack suspects", each of which contains a confidence level P attack and face feature two fields, and initialized, initially empty;

[0045] Step S2: extract the face region with the MTCNN face detection algorithm;

[0046] Step S3: Use the neural network model to calculate the living body probability of a single frame of face, and set it as P live ;

[0047] Step S4: Calculate the facial feature value;

[0048] Step S5: Match the "attack suspect" according to the facial feature value. The specific matching process includes:

[0049] Step S51: Traverse the list of "attack suspects", and compare the similarity of facial features, which is higher than the threshold P live_threshold , locked as "current attack suspect";

[0050] Step S52: If it does not exist, add “attack suspect”, confi...

Embodiment 2

[0057] In this embodiment, a living body detection auxiliary device for a face recognition system is provided, including:

[0058] The "attack suspect" list initialization module is used to establish a "attack suspect" list, each attack suspect contains a confidence level P attack and face feature two fields, and initialized, initially empty;

[0059] The face area extraction module is used to extract the face area by using the face detection algorithm;

[0060] The living body probability calculation module of a single frame of face is used to calculate the living body probability of a single frame of face by using the neural network model, set as P live ;

[0061] The face feature value calculation module is used to calculate the face feature value;

[0062] The "attack suspect" matching module is used to match the "attack suspect" according to the facial feature value. The specific matching process includes:

[0063] Traverse the list of "attack suspects" and compare th...

Embodiment 3

[0072] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, any one of the embodiments in the first embodiment can be implemented.

[0073] Since the electronic device introduced in this embodiment is the device used to implement the method in the first embodiment of the present application, based on the method introduced in the first embodiment of the present application, those skilled in the art can understand the electronic device in this embodiment. The specific implementation manner and various modifications thereof, so how the electronic device implements the methods in the embodiments of the present application will not be described in detail here. As long as the devices used by those skilled in the art to implement the methods in the embodiments of the present application fall within the scope of the intended protection o...

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Abstract

The invention discloses a living body detection auxiliary method and device for a face recognition system, and the method comprises the steps: building an attack suspect list, and carrying out the initialization; extracting a human face region by using a human face detection algorithm; calculating the living body probability of a single-frame face by using a neural network model; calculating a face feature value; according to the face feature value, matching an attack suspect; the value of the confidence coefficient is adjusted by comparing the living probability of the suspect with a set threshold value, so that whether the current suspect is true or false is judged; attenuating the confidence coefficient of the attacking suspects along with time: traversing all attacking suspects at intervals of a period of time T, and performing confidence-attenuation step length; and when the confidence coefficient is 0, deleting the'attack suspect '. According to the method, an attack suspect list is established based on face feature value matching, and most of long-time continuous attacks can be filtered; and dynamic adjustment is performed in the matching process, so that errors caused by occasional misjudgment are avoided, and the judgment result is more stable.

Description

technical field [0001] The present invention relates to the field of computer technology, and in particular, to an auxiliary method and device for living body detection used in a face recognition system. Background technique [0002] In the process of real-time face recognition, it is necessary to be careful not to use fake faces for face recognition, so it is necessary to perform liveness detection before face recognition. [0003] Many existing live detection algorithms are based on single-frame images. The specific method is to first perform face detection on the picture and then crop the face area, and then input the face area into the living body detection model to obtain the result. Since the results of single-frame image recognition often cannot have very high accuracy, when an attacker continuously conducts live attacks on the scene for a long time, there is a certain probability that the detection will break through at a certain moment. The longer the time, the hig...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V40/40G06V40/16G06K9/62G06N3/04G06V10/74G06V10/75G06V10/82
CPCG06N3/045G06F18/22
Inventor 吴振文卢云飞高如正
Owner XIAMEN STAR SMART TECH
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