A color-based tracking by Kalman particle filter

Yoshinori Satoh, Takayuki Okatani, Koichiro Deguchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

33 Citations (Scopus)

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 effectiveness of this method.

Original languageEnglish
Title of host publicationProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
EditorsJ. Kittler, M. Petrou, M. Nixon
Pages502-505
Number of pages4
DOIs
Publication statusPublished - 2004 Dec 20
EventProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 - Cambridge, United Kingdom
Duration: 2004 Aug 232004 Aug 26

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume3
ISSN (Print)1051-4651

Other

OtherProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
CountryUnited Kingdom
CityCambridge
Period04/8/2304/8/26

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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