Feature Matching using CO-Inertia Analysis for People Tracking

Srinidhi Mukanahallipatna Simha, Duc Phu Chau, Francois Bremond

2014

Abstract

Robust object tracking is a challenging computer vision problem due to dynamic changes in object pose, illumination, appearance and occlusions. Tracking objects between frames requires accurate matching of their features. We investigate real time matching of mobile object features for frame to frame tracking. This paper presents a new feature matching approach between objects for tracking that incorporates one of the multivariate analysis method called Co-Inertia Analysis abbreviated as COIA. This approach is being introduced to compute the similarity between Histogram of Oriented Gradients (HOG) features of the tracked objects. Experiments conducted shows the effectiveness of this approach for mobile object feature tracking.

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Paper Citation


in Harvard Style

Mukanahallipatna Simha S., Chau D. and Bremond F. (2014). Feature Matching using CO-Inertia Analysis for People Tracking . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-009-3, pages 280-287. DOI: 10.5220/0004669502800287


in Bibtex Style

@conference{visapp14,
author={Srinidhi Mukanahallipatna Simha and Duc Phu Chau and Francois Bremond},
title={Feature Matching using CO-Inertia Analysis for People Tracking},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={280-287},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004669502800287},
isbn={978-989-758-009-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)
TI - Feature Matching using CO-Inertia Analysis for People Tracking
SN - 978-989-758-009-3
AU - Mukanahallipatna Simha S.
AU - Chau D.
AU - Bremond F.
PY - 2014
SP - 280
EP - 287
DO - 10.5220/0004669502800287