DocumentCode :
419804
Title :
A color-based tracking by Kalman particle filter
Author :
Satoh, Yoshinori ; Okatani, Takayuki ; Deguchi, Koichiro
Author_Institution :
Graduate Sch. of Inf. Sci., Tohoku Univ., Sendai, Japan
Volume :
3
fYear :
2004
fDate :
23-26 Aug. 2004
Firstpage :
502
Abstract :
In this paper, a method for real-time tracking of moving objects is proposed. We applied Kalman particle filter (KPF) to color-based tracking. This KPF is a particle filter including the principle of Kalman filter, and it was adopted to the object contour tracking. We modified this KPF for color-based tracking. This modified KPF can approximate the probabilistic density of the position of the tracked object properly and needs fewer particles for tracking than conventional particle filters. We made experiments to confirm the effectiveness of this method.
Keywords :
Kalman filters; approximation theory; image colour analysis; image motion analysis; object detection; probability; tracking filters; Kalman particle filter; color based tracking; moving object tracking; object contour tracking; probabilistic density approximation; real time tracking method; Colored noise; Filtering; Image sampling; Image sequences; Kalman filters; Monte Carlo methods; Particle filters; Particle tracking; Probability; Statistical analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
ISSN :
1051-4651
Print_ISBN :
0-7695-2128-2
Type :
conf
DOI :
10.1109/ICPR.2004.1334576
Filename :
1334576
Link To Document :
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