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