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Incremental learning on trajectory clustering

Abstract : Scene understanding corresponds to the real time process of perceiving, analysing and elaborating an interpretation of a 3D dynamic scene observed through a network of cameras. The whole challenge consists in managing this huge amount of information and in structuring all the knowledge. On-line Clustering is an efficient manner to process such huge amounts of data. On-line processing is indeed an important capability required to perform monitoring and behaviour analysis on a long-term basis. In this paper we show how a simple clustering algorithm can be tuned to perform on-line. The system works by finding the main trajectory patterns of people in the video. We present results obtained on real videos corresponding to the monitoring of the Toulouse airport in France.
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Contributor : Jose Luis Patino Vilchis Connect in order to contact the contributor
Submitted on : Friday, July 16, 2010 - 2:44:07 PM
Last modification on : Friday, February 4, 2022 - 3:18:43 AM
Long-term archiving on: : Friday, October 22, 2010 - 2:51:05 PM


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  • HAL Id : inria-00503059, version 1



Jose Luis Patino Vilchis, François Bremond, Monique Thonnat. Incremental learning on trajectory clustering. Dr. Paolo Remagnino. Intelligent Paradigms in Safety and Security, Springer-Verlag, 2010. ⟨inria-00503059⟩



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