DocumentCode :
1894938
Title :
A New Resampling Strategy about Particle Filter Algorithm Applied in Monte Carlo Framework
Author :
Wu, Gang ; Tang, Zhenmin
Author_Institution :
Sch. of Comput. Sci. & Technol., Nanjing Univ. of Sci. & Technol., Nanjing, China
Volume :
1
fYear :
2009
fDate :
10-11 Oct. 2009
Firstpage :
507
Lastpage :
510
Abstract :
In this paper we propose a new resampling strategy about particle filter algorithm for tracking object in video sequence. We incorporate the new resampling strategy and adaptive elliptical template with the classical particle filter algorithm. We apply enhanced algorithm to track selected object in a standard video and demonstrate its performance compared with the algorithm proposed by K. Nummiaro. Experimental results show that the proposed particle filter algorithm improves the efficiency of tracking system, while it is unfluctuating even if the surroundings of visual tracking are under heavy fog.
Keywords :
Monte Carlo methods; image sampling; image sequences; particle filtering (numerical methods); tracking; video signal processing; Monte Carlo framework; adaptive elliptical template; object tracking; particle filter algorithm; resampling strategy; video sequence; visual tracking; Automation; Computer science; Computer vision; Electronic mail; Military computing; Monte Carlo methods; Particle filters; Particle tracking; Proposals; Video sequences;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Conference_Location :
Changsha, Hunan
Print_ISBN :
978-0-7695-3804-4
Type :
conf
DOI :
10.1109/ICICTA.2009.129
Filename :
5287603
Link To Document :
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