Gestion de la variabilité morphologique pour la reconnaissance de gestes naturels à partir de données 3D

Abstract : Recognition of natural movements is of utmost importance in the implementation of intelligent and effective Human-Machine Interfaces for virtual environments. It allows the user to behave naturally and the system to recognize its body movements in the same way a human might perceive it. This task is complex, because it addresses several challenges : take account of the specificities of the motion capture system, manage kinematic variability in motion performance, and finally take account of the morphological differences between individuals, so that actions of any new user can be recognized. Moreover, due to the interactive nature of virtual environments, this recognition must be achieved in real-time without waiting for the motion end. The literature offers many methods to meet the first two challenges. But the management of the morphological variability is not dealt. In this thesis, we propose a description of the movement to address this issue and we evaluate its ability to recognize the movements of an unknown user. Finally, we propose a new method to take advantage of this representation in early motion recognition
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Graphics [cs.GR]. Université Rennes 2, 2012. French. <NNT : 2012REN20062>


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Anthony Sorel. Gestion de la variabilité morphologique pour la reconnaissance de gestes naturels à partir de données 3D. Graphics [cs.GR]. Université Rennes 2, 2012. French. <NNT : 2012REN20062>. <tel-00763619v2>

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