camshift和KLT算法在实时人脸检测和跟踪应用中的比较研究

Debmalya Chatterjee, S. Chandran
{"title":"camshift和KLT算法在实时人脸检测和跟踪应用中的比较研究","authors":"Debmalya Chatterjee, S. Chandran","doi":"10.1109/ICRCICN.2016.7813552","DOIUrl":null,"url":null,"abstract":"Face detection and tracking is one of the emerging research areas in the image analysis and computer vision systems. This face detection and tracking helps local security forces to investigate crime incidents. This paper describes a face tracking framework that is capable of tracking a face in real time rapidly frame by frame. Camshift algorithm and KLT algorithm implemented and a comparison study between these two algorithms has been described in this paper. A real time video is experimented using these two algorithms for face detection and tracking. The experimental results show that the KLT algorithm performance is better than the Camshift algorithm in detecting the face and tracking the face. In this article it has been shown how the KLT algorithm proved to be better tracking algorithm than Camshift algorithm.","PeriodicalId":254393,"journal":{"name":"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Comparative study of camshift and KLT algorithms for real time face detection and tracking applications\",\"authors\":\"Debmalya Chatterjee, S. Chandran\",\"doi\":\"10.1109/ICRCICN.2016.7813552\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Face detection and tracking is one of the emerging research areas in the image analysis and computer vision systems. This face detection and tracking helps local security forces to investigate crime incidents. This paper describes a face tracking framework that is capable of tracking a face in real time rapidly frame by frame. Camshift algorithm and KLT algorithm implemented and a comparison study between these two algorithms has been described in this paper. A real time video is experimented using these two algorithms for face detection and tracking. The experimental results show that the KLT algorithm performance is better than the Camshift algorithm in detecting the face and tracking the face. In this article it has been shown how the KLT algorithm proved to be better tracking algorithm than Camshift algorithm.\",\"PeriodicalId\":254393,\"journal\":{\"name\":\"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRCICN.2016.7813552\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRCICN.2016.7813552","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17

摘要

人脸检测与跟踪是图像分析和计算机视觉系统中一个新兴的研究领域。这种面部检测和追踪有助于当地安全部队调查犯罪事件。本文描述了一种能够实时快速逐帧跟踪人脸的人脸跟踪框架。本文实现了Camshift算法和KLT算法,并对这两种算法进行了比较研究。利用这两种算法对一个实时视频进行了人脸检测和跟踪实验。实验结果表明,KLT算法在人脸检测和人脸跟踪方面的性能优于Camshift算法。本文证明了KLT算法是比Camshift算法更好的跟踪算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative study of camshift and KLT algorithms for real time face detection and tracking applications
Face detection and tracking is one of the emerging research areas in the image analysis and computer vision systems. This face detection and tracking helps local security forces to investigate crime incidents. This paper describes a face tracking framework that is capable of tracking a face in real time rapidly frame by frame. Camshift algorithm and KLT algorithm implemented and a comparison study between these two algorithms has been described in this paper. A real time video is experimented using these two algorithms for face detection and tracking. The experimental results show that the KLT algorithm performance is better than the Camshift algorithm in detecting the face and tracking the face. In this article it has been shown how the KLT algorithm proved to be better tracking algorithm than Camshift algorithm.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信