期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

引入前帧加权采样的粒子滤波目标跟踪算法 被引量：5

Particle Filter Algorithm Imported Weighted Sampling about Pre-frame in Object Tracking
在线阅读 下载PDF
导出
摘要 根据相邻帧间信息的强关联性,提出一种引入前帧加权采样的粒子滤波目标跟踪算法,解决了传统采样重要性重采样(SIR)算法由于引进提议分布(Proposal distribution)而需要严重依赖目标的系统状态模型的问题,可以理想跟踪运动状态不规则的目标。该算法提出的引入前帧加权采样思想不仅仅局限于基于序列图像的跟踪,而且可以推广到其它相关的领域,具有普适性和实用性。 Based on the strong relationship about frames near by, the Author brought forward an particle filter algorithm importing weighted sampling about pre-frame in object tracking. The algorithm resolves the trickiness in traditional SIR algorithm which depends on state-model acutely by importing proposal distribution. The algorithm can track object which movement is irregular. The thought on weighted sampling about pre-frame not only can be applied in object tracking based sequential images, but also can be extended to other fields. The method is universal and practical.
作者 吴刚 唐振民 耿烽 程勇
机构地区 南京理工大学计算机科学与技术学院 南京工程学院
出处 《计算机科学》 CSCD 北大核心 2009年第8期215-216,246,共3页 Computer Science
关键词 加权采样 粒子滤波 目标跟踪 序列图像 不规则 Weighted sampling, Particle filter, Object tracking, Sequential images, Irregular
分类号 TP391.4 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献7

  • 1王亮,胡卫明,谭铁牛.人运动的视觉分析综述[J].计算机学报,2002,25(3):225-237. 被引量：277
  • 2Horn B. Optical flow[J]. Artificial Intelligence, 1981, 17:185- 203.
  • 3Nummiaro K, Koller-Meier E, Gool L J V. An adaptive colorbased particle filter[J]. Image Vision Comput, 2003,21 (1): 99- 110.
  • 4Vander Merwe R, Doucet A, de Freitas N, et al. The Unscented Particle Filte[R]. CUED/F-INPENG/TR 380. London: Cambridge University Engineering Department, 2000.
  • 5Gordan N, Salmond D, Smith A. A novel approach to nonlinear/ nonGaussian Bayesian state estimation[J]. IEEE Proeeedings on Radar and Signal Processing, 2005,118 : 187-113.
  • 6Doucet A , de Freitas N , Gordon N. Sequential Monte Carlo Methods in Practice[M]. New York: Springer-Verlag, 2001.
  • 7汤思维,陈卫东,曹其新.移动机器人多目标彩色视觉跟踪系统[J].机器人,2003,25(1):10-14. 被引量：22

二级参考文献106

  • 1[25]Kohle M, Merkl D, Kastner J. Clinical gait analysis by neural networks: Issues and experiences. In: Proc IEEE Symposium on Computer-Based Medical Systems, Maribor, Slovenia, 1997. 138-143
  • 2[26]Meyer D, Denzler J, Niemann H. Model based extraction of articulated objects in image sequences for gait analysis. In: Proc IEEE International Conference on Image Processing, Santa Barbara, California 1997. 78-81
  • 3[27]McKenna S et al. Tracking groups of people. Computer Vision and Image Understanding, 2000, 80(1):42-56
  • 4[28]Karmann K, Brandt A. Moving object recognition using an adaptive background memory. In: Cappellini V ed. Time-varying Image Processing and Moving Object Recognition. 2. Elsevier, Amsterdam, The Netherlands, 1990
  • 5[29]Kilger M. A shadow handler in a video-based real-time traffic monitoring system. In: Proc IEEE Workshop on Applications of Computer Vision, Palm Springs, CA, 1992.1060-1066
  • 6[30]Stauffer C, Grimson W. Adaptive background mixture models for real-time tracking. In: Proc IEEE Conference on Computer Vision and Pattern Recognition, Fort Collins, Colorado, 1999, 2:246-252
  • 7[31]Wren C, Azarbayejani A, Darrell T, Pentland A. Pfinder: Real-time tracking of the human body. IEEE Trans on Pattern Analysis and Machine Intelligence, 1997, 19(7):780-785
  • 8[32]Arseneau S, Cooperstock J. Real-time image segmentation for action recognition. In: Proc IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, Victoria, Canada, 1999. 86-89
  • 9[33]Sun H, Feng T, Tan T. Robust extraction of moving objects from image sequences. In: Proc the Fourth Asian Conference on Computer Vision, Taiwan, 2000.961-964
  • 10[34]Lipton A, Fujiyoshi H, Patil R. Moving target classification and tracking from real-time video. In: Proc IEEE Workshop on Applications of Computer Vision, Princeton, NJ, 1998. 8-14

共引文献297

同被引文献46

  • 1王浩,杨峰,姚宏亮.离散动态贝叶斯网络的进化粒子滤波推理算法[J].计算机研究与发展,2008,45(z1):295-299. 被引量：5
  • 2柴霖,袁建平,罗建军,方群,岳晓奎.非线性估计理论的最新进展[J].宇航学报,2005,26(3):380-384. 被引量：37
  • 3邹国辉,敬忠良,胡洪涛.基于优化组合重采样的粒子滤波算法[J].上海交通大学学报,2006,40(7):1135-1139. 被引量：43
  • 4许士芳,谢立,刘济林.基于MCMC粒子滤波的机器人定位[J].浙江大学学报（工学版）,2007,41(7):1083-1087. 被引量：12
  • 5Gordan N, Salmond D, Smith A.Novel approach to nonlinear non-Gaussian Bayesian state estimation[J].IEEE Proceedings on Radar and Signal Processing, 1993,140:107-113.
  • 6Liu J, Chen R.Sequential Monte Carlo methods for dynamic systems[J].Jour of Amer Stat Assoc, 1998,93 : 1031-1041.
  • 7Isard M, Blake A.Visual tracking by stochastic propagation of conditional density[C]//Proc 4th European Conf Computer Vision, 1996:343-356.
  • 8Carpenter J, Clifford P,Feamhead P.An improved particle filter for non-linear problems[J].IEEE Proc Radar Sonar Navigation, 1999,146:2-7.
  • 9Nummiaro K, Koller-Meier E, Gool L J V.An adaptive color-based particle filter[J].Image Vision Comput, 2003, 21 ( 1 ) : 99-110.
  • 10Leoputra W, Tan T, Lira F L. Non-overlapping Dstributed Tracking Using Particle Fiher[C]//International Conference on Pattern Recognition(ICPR). 2006 : 181-185.

引证文献5

二级引证文献7

计算机科学
2009年 第8期

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