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Détection de la présence humaine par vision

Abstract : The work presented in this manuscript deals with people detection and activity analysis in images sequences. This work has been done in the PRISME institut within the framework of the CAPTHOM project of the French Cluster S2E2. After a state of the art on video analysis and a comparative study of several video surveillance tools, we present the people detection method proposed within the framework of the CAPTHOM project. This method is based on three steps : change detection, mobile objects tracking and classification. Each steps is described in this thesis. The system was assessed on a wide videos dataset. Then, we present methods used to obtain other high-level information concerning the activity of detected persons. A criterion for characterizing their activity is presented. Then, a multi-sensors stereovision system combining an infrared and a daylight camera is used to increase performances of the people detection system but also to localize persons in the 3D space and so build the moving cartography. Finally, an abnormal events detection method based on statistics about spatio-temporal foreground pixel distribution is presented. These proposed methods offer robust and efficient solutions on high-level information extraction from images sequences.
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Submitted on : Wednesday, June 9, 2010 - 3:06:08 PM
Last modification on : Thursday, March 5, 2020 - 6:49:29 PM
Long-term archiving on: : Friday, September 17, 2010 - 1:27:43 PM


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  • HAL Id : tel-00490803, version 1


Yannick Benezeth. Détection de la présence humaine par vision. Autre. Université d'Orléans, 2009. Français. ⟨NNT : 2009ORLE2050⟩. ⟨tel-00490803⟩



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