Robust Tracking and Object Classification Towards Automated Video Surveillance

Abstract

This paper addresses some of the key issues in computer vision that contribute to automated visual events analysis in video surveillance applications. The objectives are to robustly segment and track multiple objects in the cluttered dynamic scene, and, if required, further classify the objects into several categories. There are two major contributions… (More)
DOI: 10.1007/978-3-540-30126-4_57

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Cite this paper

@inproceedings{Landabaso2004RobustTA, title={Robust Tracking and Object Classification Towards Automated Video Surveillance}, author={Jos{\'e} Luis Landabaso and Li-Qun Xu and Montse Pard{\`a}s}, booktitle={ICIAR}, year={2004} }