Object Tracking Algorithm Based on Meanshift Algorithm Combining with Motion Vector Analysis

Gang Tian, Rui-min Hu, Zhong-yuan Wang, Li Zhu
{"title":"Object Tracking Algorithm Based on Meanshift Algorithm Combining with Motion Vector Analysis","authors":"Gang Tian, Rui-min Hu, Zhong-yuan Wang, Li Zhu","doi":"10.1109/ETCS.2009.225","DOIUrl":null,"url":null,"abstract":"Mean shift algorithm doesn't use the target’s motion direction and speed information in process of object tracking. When the target’s speed is so fast it easily fails to track the target. So a new object tracking algorithm combining Mean shift algorithm with Motion Vector analysis is proposed in this paper. By statistical analysis of the motion vector get from video encoding process, we can get the motion direction and velocity of target, which can be used to correct the central point of the motion candidate region of Mean shift, making the search position is more close to the actual centre of the target. This method can not only track the fast moving target effectively, but also reduce the number of iterative convergence times to improve the efficiency of operations. The algorithm is already use in our intelligent video surveillance equipment in which the operation of video encoding and object tracking is executed in one chip, and the experimental results show that it is feasible and effective.","PeriodicalId":422513,"journal":{"name":"2009 First International Workshop on Education Technology and Computer Science","volume":"150 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 First International Workshop on Education Technology and Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETCS.2009.225","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18

Abstract

Mean shift algorithm doesn't use the target’s motion direction and speed information in process of object tracking. When the target’s speed is so fast it easily fails to track the target. So a new object tracking algorithm combining Mean shift algorithm with Motion Vector analysis is proposed in this paper. By statistical analysis of the motion vector get from video encoding process, we can get the motion direction and velocity of target, which can be used to correct the central point of the motion candidate region of Mean shift, making the search position is more close to the actual centre of the target. This method can not only track the fast moving target effectively, but also reduce the number of iterative convergence times to improve the efficiency of operations. The algorithm is already use in our intelligent video surveillance equipment in which the operation of video encoding and object tracking is executed in one chip, and the experimental results show that it is feasible and effective.
基于Meanshift算法和运动矢量分析的目标跟踪算法
均值移位算法在目标跟踪过程中不使用目标的运动方向和速度信息。当目标速度如此之快时,它很容易无法跟踪目标。为此,本文提出了一种将Mean shift算法与运动矢量分析相结合的目标跟踪算法。通过对视频编码过程中得到的运动矢量进行统计分析,得到目标的运动方向和运动速度,从而对Mean shift运动候选区域的中心点进行校正,使搜索位置更接近目标的实际中心。该方法既能有效跟踪快速运动目标,又能减少迭代收敛次数,提高运算效率。该算法已应用于我国智能视频监控设备中,实现了视频编码和目标跟踪在一个芯片上完成,实验结果表明了该算法的可行性和有效性。
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