Face recognition method based on deep learning in monitoring environment

Abstract

The invention relates to the field of computer visions, and proposes a face recognition method based on deep learning in a monitoring environment. The method comprises the following steps: building aface feature database, and performing feature extraction and feature comparison on faces in a video, thus face detection and face recognition are achieved based on an MTCNN network and a Sphereface network respectively; and by adding affine transformation, increasing the diversity of a data set, network clipping, network sparsification and layer-by-layer quantization, the problems of low recognition accuracy of a traditional face recognition method, differences in recognition accuracy between East and West faces, and excessive bandwidth required for the face recognition technology based on deep learning are mainly solved. Experiments show that the face recognition method proposed by the invention can be used in the monitoring environment and has higher recognition accuracy.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to a face recognition method based on MTCNN and Sphereface in a monitoring environment. Background technique [0002] Face recognition is a biometric identification technology based on human facial feature information, that is, a camera or camera is used to collect images or video streams containing human faces and automatically detect and track human faces in the images, and then detect the detected Face recognition is realized by extracting features from the face. The human face is as inherent as other biological characteristics of the human body. Its uniqueness and good characteristics that are not easy to be copied provide the necessary premise for identification. In addition, compared with other types of biometrics, face recognition is also non-mandatory. , concurrency and other characteristics, so face recognition technology is widely used in various aspects, such as household ...

AI Technical Summary

Problems solved by technology

In particular, on the basis of the existing face detection and recognition technology, the present invention mainly solves the problem of low recognition accuracy of traditional face recognition methods, excessive bandwidth required by face recognition technology based on deep learning, and the difficulty of recognizing people from the East and the West. There is a problem with the difference in the accuracy of face recognition

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