AI Techniques for VSIS Human Tracker

Abstract : The aim of this work is to track humans in a known environment. The input data are pre-segmented video streams captured with a fixed camera.  In this paper we propose a new approach to the problem of simple hypothesis non-delayed human tracking.  Furthermore the approach handles simultaneously and in a unified manner the actual similarity matching and the associated real-world problems of entries, exits, occlusions and false detections (noise). Results on visual surveillance applications for security in metro stations , security in banks and monitoring in offices are shown. Quantitative results of this method in terms of time performance are presented.
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Rapport
RR-4138, INRIA. 2001
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https://hal.inria.fr/inria-00072488
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Soumis le : mercredi 24 mai 2006 - 10:06:58
Dernière modification le : samedi 17 septembre 2016 - 01:27:24
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Nathanaël Rota, Robert Stahr, Monique Thonnat. AI Techniques for VSIS Human Tracker. RR-4138, INRIA. 2001. 〈inria-00072488〉

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