A Self-adaptive Likelihood Function for Tracking with Particle Filter

Séverine Dubuisson, Myriam Robert-Seidowsky, Jonathan Fabrizio

2015

Abstract

The particle filter is known to be efficient for visual tracking. However, its parameters are empirically fixed, depending on the target application, the video sequences and the context. In this paper, we introduce a new algorithm which automatically adjusts online two majors of them: the correction and the propagation parameters. Our purpose is to determine, for each frame of a video, the optimal value of the correction parameter and to adjust the propagation one to improve the tracking performance. On one hand, our experimental results show that the common settings of particle filter are sub-optimal. On another hand, we prove that our approach achieves a lower tracking error without needing to tune these parameters. Our adaptive method allows to track objects in complex conditions (illumination changes, cluttered background, etc.) without adding any computational cost compared to the common usage with fixed parameters.

Paper Citation

in Harvard Style

Dubuisson S., Robert-Seidowsky M. and Fabrizio J. (2015). A Self-adaptive Likelihood Function for Tracking with Particle Filter . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-091-8, pages 446-453. DOI: 10.5220/0005260004460453

in Bibtex Style

@conference{visapp15,
author={Séverine Dubuisson and Myriam Robert-Seidowsky and Jonathan Fabrizio},
title={A Self-adaptive Likelihood Function for Tracking with Particle Filter},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={446-453},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005260004460453},
isbn={978-989-758-091-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)
TI - A Self-adaptive Likelihood Function for Tracking with Particle Filter
SN - 978-989-758-091-8
AU - Dubuisson S.
AU - Robert-Seidowsky M.
AU - Fabrizio J.
PY - 2015
SP - 446
EP - 453
DO - 10.5220/0005260004460453