现代信息科技2024，Vol.8Issue(1)：89-93,5.DOI:10.19850/j.cnki.2096-4706.2024.01.018
基于改进稠密网络的视频监控人脸识别算法研究
Research on Video Surveillance Face Recognition Algorithm Based on Improved Dense Network
余鸣1
作者信息
- 1. 曲靖职业技术学院 信息技术系,云南 曲靖 655000
- 折叠
摘要
Abstract
In order to improve the ability of face recognition in video surveillance,it studies the use of motion history image algorithm to realize human tracking,and proposes an improved dense network.The results show that the tracking accuracy of the human tracking algorithm used in the study is as high as 99.5%,and the recognition accuracy of the proposed recognition algorithm can be above 99.7%,and can show high recognition accuracy for faces with different expression features.The above results show that the improved dense network can effectively improve the face recognition ability of video surveillance,which is of great significance to the intelligent development of urban surveillance.关键词
视频监控/运动历史图像算法/改进稠密网络/人体跟踪/人脸识别Key words
video surveillance/motion history image algorithm/improved dense network/human tracking/face recognition分类
信息技术与安全科学引用本文复制引用
余鸣..基于改进稠密网络的视频监控人脸识别算法研究[J].现代信息科技,2024,8(1):89-93,5.
