Face Recognition Based on Depth-Learning and Non-Collaborative Method

Abstract

The invention discloses a non-cooperative face recognition method based on depth learning, which comprises the following steps: 1, generating a depth learning network training data set; 2, respectively construct a detection depth learning network and a recognition depth learn network; 3, respectively train a detection depth learning network and a recognition depth learn network; 4, prepare a non-coordinated face feature database; 5, that camera sample the video stream in real time; 6, detect and tracking that face region of the image; 7, feature match; 8. Face Recognition. By introducing a tracking algorithm in the traditional process of detecting and recognizing faces, the invention can continuously identify and analyze the same person, not only can the non-cooperative face be recognizedquickly, but also the occluded and deformed face has a better recognition rate, and can be used for recognizing the non-cooperative photographed face under the video surveillance environment.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a non-cooperative face recognition method based on deep learning in the technical field of pattern recognition. The present invention can be used to recognize faces that are not photographed in a video surveillance environment technical background [0002] Face recognition is a kind of biometric recognition technology based on human facial feature information. It analyzes the face image by computer, extracts effective information from the image and automatically identifies it. Face recognition technology is widely used in security systems and Human-computer interaction and other aspects have become one of the important research topics in the field of computer vision and pattern recognition. [0003] Compared with the traditional method, the deep learning method adopts a deeper network structure and uses a large amount of data to drive training, and has made signif...

AI Technical Summary

Problems solved by technology

The disadvantage of this method is that it is impossible to quickly identify multiple people in real time, because the ID card detection equipment must be used to detect the ID card during the test. This step can only identify one person at a time, and because the face image in the buffer pool is only Compared with a single photo of the ID card, if the angle of the image collected in the buffer pool is not standard or blocked, the recognition effect will be poor

The disadvantage of this method is that it only recognizes a single detected image, instead of dynamically analyzing the detected images within a period of time, which is easy to cause misrecognition and the accuracy rate is not high

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