Object tracking Based on Local Structure Orientation

DOI

10.2991/icectt-15.2015.89How to use a DOI?

Keywords

Particle filter; SPBRLSO; visual tracking; spatiogram

Abstract

In order to solve the poor robustness resulted from the pose variances, occlusion or clutter in some challenging videos, we propose a robust particle filter tracking method based on a new similarity measure SPBRLSO (spatio-bin-ratio based on the local structure orientation). First, the object tracked is represented by a histogram of the local structure orientation, and then the observation likelihood function is constructed using a spatial-bin-ratio similarity. Finally, the tracker is formed by the he observation likelihood function in the frame of the traditional particle filter tracking. Many experimental results show that the proposed method is able to robustly track the objects in visible videos and infrared videos from some challenging videos including pose variances, occlusion or clutter. Furthermore, our tracking performance is superior to other tracking methods including the VTD tracker, conventional particle filter tracker and the spatiogram tracker.

Copyright

© 2015, 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  - Ruxi Xiang
AU  - Xifang Zhu
AU  - Feng Wu
AU  - Qinquan Xu
PY  - 2015/11
DA  - 2015/11
TI  - Object tracking Based on Local Structure Orientation
BT  - Proceedings of the 2015 International Conference on Electromechanical Control Technology and Transportation
PB  - Atlantis Press
SP  - 466
EP  - 470
SN  - 2352-5401
UR  - https://doi.org/10.2991/icectt-15.2015.89
DO  - 10.2991/icectt-15.2015.89
ID  - Xiang2015/11
ER  -