Face recognition system

Abstract

The invention discloses a face recognition system, which relates to the technical field of image processing and pattern recognition. First, the gender of a face image to be recognized is determined through a deep learning method. Then, the face identity of the face image to be recognized is determined with high accuracy according to the gender identified through deep learning and based on a convolutional neural network. Finally, the facial micro expression of the face image to be recognized is determined through a binocular vision technology based on the parallax characteristic of the face image to be recognized. Face recognition based on the gender information, identity information and facial expression information of a face image to be recognized is realized. By combining the deep learning method, the convolutional neural network and the binocular vision technology, the influence of factors such as illumination and facial gesture on the face recognition rate is reduced, the amount of computation in the face recognition process is reduced, fast and high-accuracy face recognition is realized, the cost of face recognition is reduced, and the accuracy of face recognition under different facial postures is improved.

Description

technical field [0001] The invention relates to the technical fields of image processing and pattern recognition, in particular to a facial recognition system. Background technique [0002] Facial recognition technology is to identify the identity by analyzing the displacement shape and positional relationship of facial organs. It is an important biometric technology and is widely used in security, access control, monitoring and other fields. The main algorithms of facial recognition technology include facial recognition methods based on template matching of geometric features, facial recognition methods based on geometric features, facial recognition methods based on sample learning, and facial recognition methods based on texture features. Among them, the facial recognition method based on facial texture features mainly relies on LBP (Local Binary Pattern), that is, local binary pattern for facial feature extraction. [0003] At present, facial recognition systems are div...

AI Technical Summary

Problems solved by technology

However, the 3D face recognition technology is not yet mature enough, the 3D data is too large, the calculation complexity is high, the data calculation amount is large, the face recognition rate is low, and the 3D data acquisition equipment is expensive, and the 3D data acquisition conditions are limited. Therefore, the existing technology 3D facial recognition in is difficult to generalize in practical applications

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