Trajectories extraction from image sequences based on kinematic

Ghilès Mostafaoui, C. Achard, M. Milgram
{"title":"Trajectories extraction from image sequences based on kinematic","authors":"Ghilès Mostafaoui, C. Achard, M. Milgram","doi":"10.1109/ICIAP.2003.1234089","DOIUrl":null,"url":null,"abstract":"The problem of moving person tracking, without knowledge about the number of persons in the scene, and by taking into account occlusion, under-segmentation and over-segmentation, is challenging. A first motion detection gives us regions with several segmentation problems due to bad acquisition conditions. The tracking step, which has to manage all these problems, is realized with the EM algorithm (expectation maximization). It uses a kinematic model: we suppose a rectilinear and uniform apparent motion, this hypothesis seems very restrictive but remains locally accurate in most applications. Good results are obtained with this approach on several sequences, without any initialization.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIAP.2003.1234089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The problem of moving person tracking, without knowledge about the number of persons in the scene, and by taking into account occlusion, under-segmentation and over-segmentation, is challenging. A first motion detection gives us regions with several segmentation problems due to bad acquisition conditions. The tracking step, which has to manage all these problems, is realized with the EM algorithm (expectation maximization). It uses a kinematic model: we suppose a rectilinear and uniform apparent motion, this hypothesis seems very restrictive but remains locally accurate in most applications. Good results are obtained with this approach on several sequences, without any initialization.
基于运动学的图像序列轨迹提取
在不知道场景中有多少人的情况下,并考虑到遮挡、分割不足和过度分割的情况下,移动人员跟踪的问题是具有挑战性的。第一次运动检测给了我们一些由于采集条件不好而存在分割问题的区域。跟踪步骤采用期望最大化算法(EM)实现,该算法需要处理所有这些问题。它使用一个运动学模型:我们假设一个直线和均匀的表观运动,这个假设似乎非常严格,但在大多数应用中仍然是局部准确的。该方法在不进行任何初始化的情况下,对多个序列都得到了较好的结果。
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 求助全文
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:481959085
Book学术官方微信