Human face living body detection system applying double-branch three-dimensional convolution model, terminal and storage medium

Abstract

The invention discloses a human face living body detection system applying a double-branch three-dimensional convolution model, a terminal and a storage medium, and belongs to the field of human faceliving body detection. The system comprises a face video acquisition module, a face video preprocessing module, a living body labeling module, a living body motion amplification module, a double-branch three-dimensional convolution living body recognition training module and a living body judgment module. The double-branch three-dimensional convolution model training module is configured with a double-branch three-dimensional convolution model and comprises a static texture information sub-module, a dynamic motion clue sub-module, a fusion sub-module and a classification sub-module; the outputs of the static texture information sub-module and the dynamic motion clue sub-module are pooled, summarized and fused through the fusion sub-module, and then a detection result is output through theclassification sub-module; the invention is mimicry and has biological significance, and has very strong robustness and generalization; a great living body detection guarantee can be provided for a face recognition system, the safety of the system is improved, and information and properties are protected from being damaged.

Description

technical field [0001] The invention relates to the field of live face detection, in particular to a live face detection system, terminal and storage medium using a dual-branch three-dimensional convolution model. Background technique [0002] As people increasingly use electronic devices such as laptops and smartphones to pay, shop, pay bills, and interact socially, there is a growing need for electronic identity verification. more. Face recognition verification stands out among many systems, and is deployed on a large scale in the life of the invention. In order to ensure security and prevent various potential hacker attacks, face liveness detection is a vital part of the face verification system. [0003] At present, the biggest problem facing live face detection algorithms is the lack of generalization. Many trained models perform well on training and corresponding test sets, but their performance in new unknown data sets is not satisfactory. The actual deployment val...

AI Technical Summary

Problems solved by technology

[0009] In order to solve the problem of poor generalization performance of the existing algorithms in the field of live face detection, it cannot be applied to unknown scenarios and attack methods, and the performance is relatively fragile and unstable in actual scenarios.

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