厦门大学学报（自然科学版）2018，Vol.57Issue(3)：438-444,7.DOI:10.6043/j.issn.0438-0479.201712010
基于视觉跟踪的实时视频人脸识别
Real-time Face Recognition in Videos Based on Visual Tracking
摘要
Abstract
At present,face recognition methods based on deep learning yield high accuracies,but their complex models recognize face slowly.To achieve the real-time face recognition in surveillance videos,we propose a real-time face recognition method in videos based on visual tracking (RFRV-VT).Firstly,this algorithm divides the surveillance video frame sequence into several groups,and each group contains face recognition frames and face tracking frames.Then,face detection method and face feature extraction method based on deep learning are used in the face recognition frame,and visual tracking method based on kernelized correlation filters (KCF)is used to speed up the recognition in the face tracking frame.This method is applied to the YouTube Faces (YTF)dataset for testing.Experimental results show that the proposed algorithm exhibits real-time performances and high recognition accuracies in videos (99.60％).关键词
视觉跟踪/人脸识别/监控视频Key words
visual tracking/face recognition/surveillance video分类
信息技术与安全科学引用本文复制引用
任梓涵,杨双远..基于视觉跟踪的实时视频人脸识别[J].厦门大学学报（自然科学版）,2018,57(3):438-444,7.基金项目
福建省自然科学基金(2015J01288) （2015J01288）
