期刊文献+

视频目标跟踪算法综述 被引量:39

Survey of Visual Object Tracking Algorithms
下载PDF
导出
摘要 介绍了视频目标跟踪算法及其研究进展,包括基于对比度分析的目标跟踪算法、基于匹配的目标跟踪算法和基于运动检测的目标跟踪算法。重点分析了目标跟踪中特征匹配、贝叶斯滤波、概率图模型和核方法的主要内容及最新进展。此外,还介绍了多特征跟踪、利用上下文信息的目标跟踪和多目标跟踪算法及其进展。 The field of visual object tracking algorithms are introduced,including visual tracking based on contrast analysis,visual tracking based on feature matching and visual tracking based on moving detection.Feature matching,Bayesian filtering,probabilistic graphical models,kernel tracking and their recent developments are analyzed.The development of multiple cues based tracking,contexts based tracking and multi-target tracking are also discussed.
出处 《电视技术》 北大核心 2010年第12期135-138,142,共5页 Video Engineering
基金 国家"863"计划项目(2006AA703405F) 福建省自然科学基金项目(2009J05141) 福建省教育厅科技计划项目(JA09040)
关键词 目标跟踪 特征匹配 贝叶斯滤波 概率图模型 均值漂移 粒子滤波 visual tracking feature matching Bayesian filtering probabilistic graphical models mean shift particle filter
  • 相关文献

参考文献27

  • 1蔡荣太,雷凯,张旭光,王延杰.基于.Net的视频跟踪仿真平台设计[J].计算机仿真,2007,24(12):181-184. 被引量:1
  • 2MAGGIO E,TAJ M,CAVALLARO A.Efficient multi-target visual tracking using random finite sets[J].IEEE Transactions on Circuits and Systems for Video Technology,2008,18(8):1016-1027.
  • 3XU X,LI R.Adaptive raoblackwellized particle filter and its evaluation for tracking in surveillance[J] /IEEE Transactions on Image Processing,2007,16(3):838-849.
  • 4LAO Y,ZHU J,ZHENG Y.Sequential particle generation for visual tracking[J].IEEE Transactions on Circuits and Systems for Video Technology,2009,19(9):1365-1378.
  • 5PAN P,SCHONFILD D.Dynamic proposal variance and optimal particle allocation in particle filtering for video tracking[J].IEEE Transaction on Circuits and Systems for Video Technology,2008,18(9):1268-1279.
  • 6BOUAYNAYA N,SCHONFELD D.On the optimality of motionbased particle filtering[J].IEEE Transactions on Circuits and Systems for Video Technology,2009,19(7):1068-1072.
  • 7IOANNIS P,EDWIN H R.Coupled prediction classification for robust visual tracking[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2010,32(9):1553-1567.
  • 8SOTO D A,REGAZZONI M C S.Bayesian tracking for video analytics[J].IEEE Signal Processing Magazine,2010,27(5):46-55.
  • 9王宇.基于Mean Shift的序列图像手势跟踪算法[J].电视技术,2010,34(6):97-99. 被引量:7
  • 10LEICHTER I,LINDENBAUM M,RIVLIN E.Mean Shift tracking with multiple reference color histograms[J].Computer Vision and Image Understanding,2010,114(3):400-408.

二级参考文献14

  • 1陈凯,张福欣.基于计算机系统的图像跟踪算法仿真平台设计[J].电光系统,2004(3):48-51. 被引量:1
  • 2缑林峰,马静,王镛根.基于VC++.Net与Matlab的燃油调节器仿真[J].计算机仿真,2005,22(12):41-44. 被引量:5
  • 3周瑞琪,江加和,赵玉侠.一种实用的快速相关跟踪算法[J].计算机仿真,2006,23(2):93-95. 被引量:2
  • 4邵文坤,黄爱民,韦庆.动态场景下的运动目标跟踪方法研究[J].计算机仿真,2006,23(5):181-184. 被引量:29
  • 5KAILATH T.The divergence and Bhattacharyya distance measures in signal selection[J].IEEE Trans. Comm. Tichnology, 1967 ( 15 ) :52-60.
  • 6RICHARD O D,PETER E H,DAVID G S. Pattern Classification[M].2nd Ed.李宏东,姚天翔,译.北京:机械工业出版社,2003.
  • 7WU Y,HUANG T S. Robust visual tracking by integrating multiple cues based on co-inference learning[J].International Journal of Computer Vision ,2004,58( 1 ) :55-71.
  • 8TRIESCH J, MALSBURG C V D.Self-organized integrationof adaptive visual cues for face tracking [C]//Proc. the Fourth International Conference on Automatic Face and Gesture Recognition. Grenoble, France : [s.n.], 2000 : 102-107.
  • 9COMANICIU D,RAMESH V,MEER P. Kernel-based object tracking [J].Pattern Analysis and Machine Intelligence, 2003,25 (5):564-577.
  • 10COMANICIU D,RAMESH V,MEER P. Real-time tracking of non- rigid objects using mean shift[J].IEEE Computer Vision and Pattern Recognition, 2000 (2) : 142-149.

共引文献6

同被引文献314

引证文献39

二级引证文献134

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部