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Title: Rule-driven object tracking in clutter and partial occlusion with model-based snakes
Authors: Tsechpenakis, Gabriel 
Rapantzikos, Konstantinos 
Tsapatsoulis, Nicolas 
Kollias, Stefanos D. 
Keywords: Model-based snakes
Object partial occlusion
Rule-driven tracking
Issue Date: 2004
Publisher: Hindawi Publishing Corporation
Source: EURASIP Journal on Applied Signal Processing, Vol. 2004, no. 1, 2004, pp. 841-860
Abstract: In the last few years it has been made clear to the research community that further improvements in classic approaches for solving low-level computer vision and image/video understanding tasks are difficult to obtain. New approaches started evolving, employing knowledge-based processing, though transforming a priori knowledge to low-level models and rules are far from being straightforward. In this paper, we examine one of the most popular active contour models, snakes, and propose a snake model, modifying terms and introducing a model-based one that eliminates basic problems through the usage of prior shape knowledge in the model. A probabilistic rule-driven utilization of the proposed model follows, being able to handle (or cope with) objects of different shapes, contour complexities and motions; different environments, indoor and outdoor; cluttered sequences; and cases where background is complex (not smooth) and when moving objects get partially occluded. The proposed method has been tested in a variety of sequences and the experimental results verify its efficiency.
ISSN: 1110-8657
DOI: 10.1155/S1110865704401103
Rights: Hindawi Publishing Corporation
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