Interactive face in vivo detection method and device based on multi-task self encoder

Abstract

The invention discloses an interactive face in vivo detection method and device based on a multi-task self encoder. The method comprises the following steps: carrying out face detection and tracking by a camera to acquire a face image; indicating a user to perform a specified action; carrying out face key point detection and face organ state judgment through the multi-task self encoder according to the acquired face image; carrying out face position tracking by the multi-task self encoder, judging whether the user performs the specified action through a video within a period of time, and meanwhile acquiring a user image; repeating steps S2-S4, and judging whether the in vivo detection is successful according to the accomplishment condition of the specified action of the user after a preset time. In the method disclosed by the invention, a key point can be positioned, and various specified actions can also be naturally judged by the multi-task self encoder, the image and video attacks in the in vivo detection can be effectively prevented without adding additional model operation.

Description

technical field [0001] The invention relates to the technical fields of pattern recognition, computer vision, face detection and alignment, etc., and in particular to an interactive face detection method and device based on deep learning. Background technique [0002] Face recognition technology has developed rapidly in recent years. Due to its ease of use, more and more occasions have begun to use face recognition technology for identity verification. Since the face recognition system is extremely vulnerable to attacks from photos and video clips, it is necessary to determine whether the collected face images are real people while comparing the collected face images with the face images in the registration database. That is, liveness detection, which is used to determine that the target is a living individual. At present, there are three common attack methods for face recognition systems: printed face photos, face images on the display screen, face masks and 3D models. Du...

AI Technical Summary

Problems solved by technology

The last category requires the participation of the user. For example, the user is required to perform a specified action, and the liveness detection is performed by verifying whether they are synchronized through the action judgment. The traditional interactive face liveness detection requires separate face key point positioning, pose estimation, and mouth detection. Various tasks such as opening and closing state judgments increase the complexity and calculation time of the model, and the general performance of the model decreases because the correlation between tasks is not considered.

Images