Video face recognition method based on aggregation adversarial network

Abstract

The invention discloses a video face recognition method based on an aggregation adversarial network, and belongs to the technical field of video face recognition. According to the method, an aggregation adversarial network constructed by an aggregation network, a discrimination network and an identification network is adopted, the aggregation network and the discrimination network form adversariallearning, and a generated image is closer to a static image of a target set in a competitive mode; and the perception loss is calculated in the high-dimensional feature space through the recognitionnetwork, so that the generated image is closer to the static image of the corresponding target set in perception performance, and the performance of the aggregation network is improved. And the discrimination network adopts a softmax multi-dimensional output form, so that not only can the authenticity of the image be judged, but also the identity category of the image can be discriminated, the identity of the generated image is enabled to be closer to a real value, the subsequent identification is enabled to be more accurate, and the identification efficiency is enabled to be higher.

Description

technical field [0001] The invention relates to a video face recognition method based on an aggregation confrontation network, and belongs to the technical field of video face recognition. Background technique [0002] Video face recognition technology, as the name suggests, is based on video for face recognition. With the increasing development of technology and demand, video face recognition technology has been applied in many fields, such as intelligent security, video surveillance, public security investigation and many other fields. [0003] Video face recognition is different from face recognition based on a single image. The query set of video face recognition is a video sequence, and its target set is usually a high-definition face image. By extracting the face features of the video sequence and Targets are matched centrally to identify the identity of the person in the video. [0004] However, in the most common video surveillance scene for video face recognition,...

AI Technical Summary

Problems solved by technology

[0006] In order to solve the problems of low efficiency and low precision in the existing video face recognition technology, the present invention provides a video face recognition method. In the recognition process, multiple low-quality video The sequence is aggregated into a single high-quality frontal face image, and the quality of the generated frontal face image is improved through confrontation learning during the aggregation process, so as to accurately perform video face recognition;

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