Color-based probabilistic tracking

Color-based probabilistic tracking (2002)

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by P. Pérez , C. Hue , J. Vermaak , M. Gangnet

Venue:	In Proc. ECCV
Citations:	157 - 3 self

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Datum	Value	Source
TITLE	Color-based probabilistic tracking	INFERENCE
AUTHOR NAME	P. Pérez	SVM HeaderParse 0.2
AUTHOR AFFIL	1 Microsoft Research, 7 JJ Thomson Av., Cambridge CB3 0FB	SVM HeaderParse 0.2
AUTHOR ADDR	UK	SVM HeaderParse 0.2
AUTHOR NAME	C. Hue	SVM HeaderParse 0.2
AUTHOR ADDR	2 Irisa, Campus de Beaulieu, F35042 Rennes Cedex, France	SVM HeaderParse 0.2
AUTHOR NAME	J. Vermaak	SVM HeaderParse 0.2
AUTHOR AFFIL	1 Microsoft Research, 7 JJ Thomson Av., Cambridge CB3 0FB	SVM HeaderParse 0.2
AUTHOR ADDR	UK	SVM HeaderParse 0.2
AUTHOR NAME	M. Gangnet	SVM HeaderParse 0.2
AUTHOR AFFIL	1 Microsoft Research, 7 JJ Thomson Av., Cambridge CB3 0FB	SVM HeaderParse 0.2
AUTHOR ADDR	UK	SVM HeaderParse 0.2
ABSTRACT	Abstract. Color-based trackers recently proposed in [3,4,5] have been proved robust and versatile for a modest computational cost. They are especially appealing for tracking tasks where the spatial structure of the tracked objects exhibits such a dramatic variability that trackers based on a space-dependent appearance reference would break down very fast. Trackers in [3,4,5] rely on the deterministic search of a window whose color content matches a reference histogram color model. Relying on the same principle of color histogram distance, but within a probabilistic framework, we introduce a new Monte Carlo tracking technique. The use of a particle filter allows us to better handle color clutter in the background, as well as complete occlusion of the tracked entities over a few frames. This probabilistic approach is very flexible and can be extended in a number of useful ways. In particular, we introduce the following ingredients: multi-part color modeling to capture a rough spatial layout ignored by global histograms, incorporation of a background color model when relevant, and extension to multiple objects. 1	SVM HeaderParse 0.2
YEAR	2002	INFERENCE
VENUE	In Proc. ECCV	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	661--675	INFERENCE
VOLUME	1	INFERENCE
CITATIONS	21 found	ParsCit 1.0