Human face living body detection method and apparatus

Abstract

The invention provides a human face living body detection method, belongs to the technical field of human face identification, and solves the problems of low human face living body detection efficiency and accuracy in the prior art. The method comprises the steps of obtaining a color image and a depth image of a to-be-detected target; determining normalized human face images corresponding to the color image and the depth image; by performing correlation analysis on the normalized human face images corresponding to the color image and the depth image, determining a correlation feature of the color image and the depth image; by performing depth consistency analysis on the normalized human face image corresponding to the depth image, determining a depth consistency feature of the depth image;and according to the correlation feature and the depth consistency feature, performing human body living body detection on the to-be-detected target. According to the method, the human body living body detection is performed in combination with color information and space information in the images of the to-be-detected target, so that the living body detection accuracy is improved.

Description

technical field [0001] The present application relates to the technical field of face recognition, and in particular to a face liveness detection method and device. Background technique [0002] Face recognition technology is more and more widely used in biometric identification devices such as attendance machines, access control systems, and electronic payment systems, which greatly facilitates people's daily life. [0003] However, with the widespread application of face recognition technology, the importance of face attack detection has become increasingly prominent. Commonly used face attack methods include: face recognition by using forged face images, face videos or face molds to pretend to be real faces. [0004] Usually, face attacks can be identified by performing face liveness detection on images to be recognized. In the prior art, commonly used face detection methods include face detection based on motion information, face detection based on texture feature anal...

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Problems solved by technology

[0005] In the research of the prior art, the applicant found that face liveness detection based on motion information combined with voice and other information takes a long time to collect features, and the detection efficiency is low; face liveness detection based on texture features, in The effect is not good on high-definition face images

[0006] In summary, the face detection methods in the prior art still need to be improved

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