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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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Submitted on : Wednesday, May 24, 2006 - 10:06:58 AM
Last modification on : Friday, February 4, 2022 - 3:18:27 AM
Long-term archiving on: : Sunday, April 4, 2010 - 11:10:10 PM


  • HAL Id : inria-00072488, version 1



Nathanaël Rota, Robert Stahr, Monique Thonnat. AI Techniques for VSIS Human Tracker. RR-4138, INRIA. 2001. ⟨inria-00072488⟩



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