An Improved Particle Filter Approach for Real-time Pedestrian Tracking in Surveillance Video

DOI

10.2991/icista.2013.35How to use a DOI?

Keywords

Pedestrian tracking, particle filter, surveillance video

Abstract

This paper presents a method for pedestrian tracking in surveillance video, and the method is based on an improved particle filter. In our algorithm, the dynamics is modeled as a second-order autoregressive process. And for the observation model, color histogram features are used for likelihood measure. The proposed color histogram method is operated on a sub-region of the target region and we explore how the background subtraction process affects the color histogram model. We further adopt rectangle filters and pixel-difference cues in the observation model to overcome the limitation of individual cue. Experiments show that the method yields better tracking performance with the improved observation model.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yaowen Guan
AU  - Xiaoou Chen
AU  - Yuqian Wu
AU  - Deshun Yang
PY  - 2013/06
DA  - 2013/06
TI  - An Improved Particle Filter Approach for Real-time Pedestrian Tracking in Surveillance Video
BT  - Proceedings of the 2013 International Conference on Information Science and Technology Applications (ICISTA-2013)
PB  - Atlantis Press
SP  - 173
EP  - 177
SN  - 1951-6851
UR  - https://doi.org/10.2991/icista.2013.35
DO  - 10.2991/icista.2013.35
ID  - Guan2013/06
ER  -