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