DocumentCode :
2633396
Title :
Target tracking using the snake particle filter
Author :
Aksel, Alla ; Acton, Scott T.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Virginia, Charlottesville, VA, USA
fYear :
2010
fDate :
23-25 May 2010
Firstpage :
33
Lastpage :
36
Abstract :
This paper presents a method, the snake particle filter (SPF), for tracking targets in video sequences. Manual or semi-automated solutions are both expensive and susceptible to error. In the SPF algorithm, automated tracking is accomplished by combining the particle filter with the snake. Here we employ the snake to establish the target shape, which is used to assign the weight for each particle in the particle filter. The snake provides a likelihood measure in the flexible particle filter framework that accommodates non-linear, non-Gaussian systems. Our results show that the SPF algorithm has an associated low RMSE value of approximately five pixels in the sequences tested for this study.
Keywords :
Gaussian processes; image resolution; particle filtering (numerical methods); target tracking; video surveillance; automated tracking; low RMSE value; manual solutions; nonGaussian systems; nonlinear systems; pixels; semiautomated solutions; snake particle filter; target shape; target tracking; video sequences; Active contours; Computer errors; Monte Carlo methods; Particle filters; Particle tracking; Shape; Target tracking; Vehicles; Video sequences; Video surveillance; Active Contours or Snakes; Particle Filter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Analysis & Interpretation (SSIAI), 2010 IEEE Southwest Symposium on
Conference_Location :
Austin, TX
Print_ISBN :
978-1-4244-7801-9
Type :
conf
DOI :
10.1109/SSIAI.2010.5483924
Filename :
5483924
Link To Document :
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