Affiliation:
1. Yangtze Normal University
2. Chongqing Normal University
Abstract
During process of objects tracking, problem of tracking box about marked objects is a major problem. Moreover, tracking of multi-objects are also difficult problems of objects tracking. This paper can tag object automatically through using motion vector of Mpeg2 to mark activities object of static video. Then, we extract multi-dimensional characteristics from initial goal of motion vector determined and made model. And accurately identify particles of larger weight to achieve purpose of accurately tracking objects through process of original value of particle filter matching observed value. As adopted methods of pattern classifying, so made feature matching between new particle and original particle are more accurate. The experiments show that the algorithm had good tracking performance and strong robustness.
Publisher
Trans Tech Publications, Ltd.
Reference10 articles.
1. M. Arulampalam, S. Maskell, N. Gordon. A Tutorial on Particle Filters for Online Non2linear/Non2Gaussian Bayesian Tracking[J]. IEEE Transactions on Signal Processing, 2002, 50 (2) : 174 - 188.
2. STRAKA O, SIMANDL M. Particle filter adaptation based on efficient sample size[C] / /Proc of the 14th IFAC Symposium on System Identification. Newcastle: IFAC Publisher, 2006: 9912996.
3. KWOK C, FOX D, MEILA M. Real-time particle filter [J]. Proceedings of the IEEE, 2004, 92 (3): 4692484.
4. HU XL, SCHON TB, LJUNG L. A basic convergence results for Particle Filtering[J]. IEEE Transactions Signal Processing, 2008, 56 (4): 133721348.
5. GAO Shi-wei , GUO Lei , YANG Ning , CHEN Liang , DU Ya-qin. A New Particle Filter Object Tracking Algorithm. JOURNAL OF SHAN GHAI J IAOTONG UNIVERSITY. 2009(3).
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