Multiple Hypotheses Multiple Levels Object Tracking

Ronan Sicre, Henri Nicolas

Abstract

This paper presents an object tracking system. Our goal is to create a real-time object tracker that can handle occlusions, track multiple objects that are rigid or deformable, and on indoor or outdoor sequences. This system is composed of two main modules: motion detection and object tracking. Motion detection is achieved using an improved Gaussian mixture model. Based on multiple hypothesis of object appearance, tracking is achieved on various levels. The core of this module uses regions local and global information to match these regions over the frame sequence. Then higher level instances are used to handle uncertainty, such as missmatches, objects disappearance, and occlusions. Finally, merges and splits are detected for further occlusions detection.

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Paper Citation


in Harvard Style

Sicre R. and Nicolas H. (2013). Multiple Hypotheses Multiple Levels Object Tracking . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-48-8, pages 355-360. DOI: 10.5220/0004183103550360


in Bibtex Style

@conference{visapp13,
author={Ronan Sicre and Henri Nicolas},
title={Multiple Hypotheses Multiple Levels Object Tracking},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={355-360},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004183103550360},
isbn={978-989-8565-48-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)
TI - Multiple Hypotheses Multiple Levels Object Tracking
SN - 978-989-8565-48-8
AU - Sicre R.
AU - Nicolas H.
PY - 2013
SP - 355
EP - 360
DO - 10.5220/0004183103550360