Object Contour Tracking in Videos by Matching Finite Mixture Models

Sydney, NSW, Australia November 22-November 24

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http://doi.ieeecomputersociety.org/10.1109/AVSS.2006.83

2006 IEEE International Conference on ...

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	Mohand Said Allili, Djemel Ziou, "Object Contour Tracking in Videos by Matching Finite Mixture Models," Advanced Video and Signal Based Surveillance, IEEE Conference on, pp. 35, 2006 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS'06), 2006.

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	@article{ 10.1109/AVSS.2006.83, author = {Mohand Said Allili and Djemel Ziou}, title = {Object Contour Tracking in Videos by Matching Finite Mixture Models}, journal ={Advanced Video and Signal Based Surveillance, IEEE Conference on}, volume = {0}, year = {2006}, isbn = {0-7695-2688-8}, pages = {35}, doi = {http://doi.ieeecomputersociety.org/10.1109/AVSS.2006.83}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

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	TY - CONF JO - Advanced Video and Signal Based Surveillance, IEEE Conference on TI - Object Contour Tracking in Videos by Matching Finite Mixture Models SN - 0-7695-2688-8 SP EP A1 - Mohand Said Allili, A1 - Djemel Ziou, PY - 2006 KW - Tracking KW - mixture of pdfs KW - color KW - texture KW - boundary KW - shape KW - level-sets. VL - 0 JA - Advanced Video and Signal Based Surveillance, IEEE Conference on ER -

Mohand Said Allili, Faculty of Science, Sherbrooke, Canada

Djemel Ziou, Faculty of Science, Sherbrooke, Canada

In this paper, we propose a novel object tracking algorithm in video sequences. The method is based on object mixture matching between successive frames of the sequence by using active contours. Only the segmentation of the objects in the first frame is required for initialization. The evolution of the object contour on a current frame aims to find the maximum fidelity of the mixture likelihood for the same object between successive frames while having the best fit of the mixture parameters to the homogenous parts of the objects. To permit for a precise and robust tracking, region, boundary and shape information are coupled in the model. The method permits for tracking multi-class objects on cluttered and non-static backgrounds. We validate our approach on examples of tracking performed on real video sequences.

Index Terms:

Tracking, mixture of pdfs, color, texture, boundary, shape, level-sets.

Citation:

Mohand Said Allili, Djemel Ziou, "Object Contour Tracking in Videos by Matching Finite Mixture Models," avss, pp.35, 2006 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS'06), 2006

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