Multi-channel network-based video human face detection and identification method

Abstract

The invention discloses a multi-channel network-based video human face detection and identification method. The method comprises the following steps of S1, performing video preprocessing: adding time information to each frame image; S2, detecting a target human face and calculating a pose coefficient; S3, correcting a human face pose: for m human faces obtained in the step S2, performing pose adjustment; S4, extracting human face features based on a deep neural network; and S5, comparing the human face features: for an input human face, obtaining eigenvectors by utilizing the step S4, matching a matching degree of an eigenvector of the input human face and a vector in a feature library by utilizing a cosine distance, and adding a class to alternative classes, and if the cosine distances between a feature of the to-be-identified human face and central features of all classes are all smaller than a set threshold phi, regarding that a database does not store information of a person, and ending the identification, wherein the cosine distance between the class and the to-be-identified human face is greater than the set threshold phi. The multi-channel network-based video human face detection and identification method with relatively high accuracy is provided.

Description

technical field [0001] The invention relates to the field of video face detection and recognition, in particular to a video face recognition method based on deep learning. Background technique [0002] Video surveillance is an important part of a security system. With the development of video sensor technology and corresponding supporting technologies, from the initial analog monitoring system, the subsequent digital-analog monitoring system, to the ip monitoring system that is now being applied, the application range of video monitoring is getting wider and wider, especially for public security The system deploys a large number of video surveillance systems to be used in public security management and suspect tracking. [0003] The rapid development of video surveillance systems has produced a large amount of surveillance video data. One of the main processing of these video data in the field of public security management and suspect tracking is to find the video files tha...

AI Technical Summary

Problems solved by technology

[0007] Judging from the existing methods, it is mainly to extract the face information of some frames in the video image, and use deep learning for training and detection and recognition. The time-space connection between the frames in the video image has not been considered. lead to lower accuracy

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