Applying 3D Human Model in a Posture Recognition System



This paper proposes an approach to recognise human postures in videosequences, 
which combines a 2D approach with a 3D human model. The 3D model is a  
realistic articulated human model which is used to obtain reference 
postures to compare with test postures. Several 2D approaches using 
different silhouette representations are compared with 
each other: projections of moving pixels on the reference axis,
Hu moments and skeletonisation. We are interested in a set of
specific postures which are representative of typical video understanding
applications. We describe results for recognition of general postures 
(e.g. standing) and detailed postures (e.g standing with one arm up) in ambiguous/optimal 
viewpoint with good/bad segmented silhouette to show the effectiveness of our approach.

Mots clé:

Human posture, 3D human model, Vision and image processing, 
Silhouette, Horizontal and vertical projections, Hu moments, Image skeletonisation

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BibTeX reference:

AUTHOR    = {Boulay, B. and Bremond, F. and Thonnat, M. },
TITLE     = {Applying 3D Human Model in a Posture Recognition System},
JOURNAL = {Pattern Recognition Letter, Special Issue on vision for Crime 
Detection and Prevention},
NUMBER = {15},
VOLUME = {27}
MONTH     = {November}, 
YEAR      = {2006}
PAGES = {1788-1796}

} --

Dernière mise à jour : 29/09/06