Human face living body detection method, related device, equipment and storage medium

Abstract

The invention discloses a human face living body detection method, which is applied to the field of artificial intelligence, and comprises the steps of obtaining an initial human face image and a human face image set corresponding to N illumination directions; obtaining N differential images according to the initial face image and the face image set; generating a normal graph and a reflectivity graph according to the N differential images and the N illumination directions; and determining a human face living body detection result according to the N difference images, the normal graph and the reflectivity graph. The invention further discloses a related device, equipment and a storage medium. Due to the fact that the three-dimensional geometrical information and the surface material information of the face image are considered at the same time, the authenticity of the face image can be recognized, and different face living body attack modes can be effectively resisted.

Description

technical field [0001] The present application relates to the field of artificial intelligence, and in particular to a face detection method, related devices, equipment and storage media. Background technique [0002] The main purpose of face liveness detection is to judge whether the current face is a real living person, so as to resist the attack of fake face. Face liveness detection is an important step before face recognition. With the application of face recognition in many important fields such as face payment and face access control, the problem of using counterfeit faces to attack face recognition has become increasingly prominent. Face liveness detection is the main technical path to resist counterfeit face attacks. [0003] At present, multiple face images are mainly used as the basis for face liveness detection. For example, if the face in the face image meets the action characteristics of blinking or opening the mouth, it is determined that the face in the image...

AI Technical Summary

Problems solved by technology

[0004] However, for high-definition printed face images or high-resolution face photos, it is difficult to distinguish whether it is a living human face. For example, use a high-resolution face photo with eyes open and a high-resolution photo with eyes closed. High-rate face photos are used as face liveness detection, and may also be mistaken for live face

It can be seen that using the current scheme for face detection is not robust, and it is difficult to resist the attack of counterfeit face

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