A Liveness Detection Method Based on Relative Attributes

Abstract

The invention relates to a living body detection method based on relative attributes, which comprises the following steps: 1) detecting the face position on each frame image in an input video; 2) obtaining key points of the human face; 3) obtaining eyes according to the obtained key points or the area of ​​the mouth; 4) judging whether the law of the attribute change value of the area obtained in step 3) in the continuous multi-frame image conforms to the law of change of the real face, if so, it is judged as a real face, if not, it is judged as false human face. Compared with the prior art, the present invention has the advantages of high detection precision, fast speed and the like.

Description

technical field [0001] The invention relates to a face detection technology, in particular to a relative attribute-based living body detection method. Background technique [0002] As a kind of identity authentication technology, face recognition has been successful in the fields of public security, attendance and access control. However, traditional face recognition technology does not consider the authenticity of the target face, so it is vulnerable to false face attacks. If the fake face attack is successful, it may cause heavy losses to users, so reliable and efficient face liveness detection technology has become an important part of the face verification system. [0003] Traditional face recognition technology often uses methods such as Fourier spectrum analysis, eye blink detection, and 3D depth estimation to judge living bodies. However, these methods are difficult to meet the requirements of the fields of finance and public security. There are two main factors: 1...

AI Technical Summary

Problems solved by technology

[0004] The performance of traditional eye-closed (or mouth-opened) classifiers is difficult to meet the needs, for example, some people's eyes are small or some people's eyes cannot be completely closed, etc.

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