Spatiotemporal segmentation and tracking of objects in color image sequences

Y. Kompatsiaris, George Mantzaras, M. Strintzis
{"title":"Spatiotemporal segmentation and tracking of objects in color image sequences","authors":"Y. Kompatsiaris, George Mantzaras, M. Strintzis","doi":"10.1109/ISCAS.2000.857355","DOIUrl":null,"url":null,"abstract":"In this paper a procedure is described for the segmentation and tracking of objects in color image sequences. For this purpose, we propose the novel procedure of K-Means with a connectivity constraint algorithm as a general segmentation algorithm combining several types of information including color, motion and compactness. In this algorithm, the use of spatiotemporal regions is introduced since a number of frames is analyzed simultaneously and as a result the same region is present in consequent frames. Experimental results in real image sequences evaluate the performance of the algorithm.","PeriodicalId":6422,"journal":{"name":"2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353)","volume":"29 1","pages":"29-32 vol.5"},"PeriodicalIF":0.0000,"publicationDate":"2000-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCAS.2000.857355","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

Abstract

In this paper a procedure is described for the segmentation and tracking of objects in color image sequences. For this purpose, we propose the novel procedure of K-Means with a connectivity constraint algorithm as a general segmentation algorithm combining several types of information including color, motion and compactness. In this algorithm, the use of spatiotemporal regions is introduced since a number of frames is analyzed simultaneously and as a result the same region is present in consequent frames. Experimental results in real image sequences evaluate the performance of the algorithm.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
彩色图像序列中目标的时空分割与跟踪
本文描述了彩色图像序列中目标的分割与跟踪方法。为此,我们提出了一种新的带有连通性约束的K-Means算法,作为一种综合了颜色、运动和紧密度等多种信息的通用分割算法。在该算法中,引入了时空区域的使用,因为同时分析了许多帧,因此在后续帧中存在相同的区域。在真实图像序列中的实验结果评价了算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A novel class A CMOS current conveyor Adaptive envelope-constrained filter design Phenomenological model of false lock in the sampling phase-locked loop A novel two-port 6T CMOS SRAM cell structure for low-voltage VLSI SRAM with single-bit-line simultaneous read-and-write access (SBLSRWA) capability Real-time calculus for scheduling hard real-time systems
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1