Analyse automatique de film - Des séquences d'images aux séquences d'actions.

Rémi Ronfard 1
1 LEAR - Learning and recognition in vision
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : I review my research activities in Video Indexing and Action Recognition and sketch a research agenda for bringing those two lines of research together to address the difficult problem of recognizing actions in movies. I first present a series of older projects in Video Indexing, starting with the DIVAN project at INA and the MPEG expert group (1998-2000), and continuing at INRIA under the VIBES project (2001-2004). This research falls under the general approach of "computational media aesthetics", where we attempt to recognize film events based on our knowledge of filming styles and conventions (cinematography and editing). This is illustrated with two applications - the automatic segmentation of TV news into topics; and the automatic indexing of movies with their scripts. I then present my more recent research in Action Recognition with the MOVI group at INRIA (2005-2008). Building upon the GRIMAGE infrastructure, I present experiments in (1) learning and recognizing a small repertoire of full body gestures in 3D using "motion history volumes"; (2) segmenting a raw stream of 3D image sequences into recognizable "primitive actions" ; and (3) using statistical models learned in 3D for recovering primitive actions and relative camera positions from a single 2D video recording of similar actions.
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Habilitation à diriger des recherches
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Rémi Ronfard. Analyse automatique de film - Des séquences d'images aux séquences d'actions.. Interface homme-machine [cs.HC]. Université de Grenoble, 2009. ⟨tel-00450230⟩

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