Reference : Estimation of human orientation based on silhouettes and machine learning principles
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Electrical & electronics engineering
http://hdl.handle.net/2268/101285
Estimation of human orientation based on silhouettes and machine learning principles
English
Pierard, Sébastien mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Télécommunications >]
Van Droogenbroeck, Marc mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Télécommunications >]
Feb-2012
International conference on pattern recognition applications and methods (ICPRAM)
51-60 (in volume 2)
Yes
No
International
International conference on pattern recognition applications and methods (ICPRAM)
02-2012
Vilamoura
Portugal
[en] Human ; Silhouette ; Machine learning ; Orientation ; Regression
[en] Estimating the orientation of the observed person is a crucial task for home entertainment, man-machine interaction, intelligent vehicles, etc. This is possible but complex with a single camera because it only provides one side view. To decrease the sensitivity to color and texture, we use the silhouette to infer the orientation. Under these conditions, we show that the only intrinsic limitation is to confuse the orientation q with the supplementary angle (that is 180°-theta), and that the shape descriptor must distinguish between mirrored images.
In this paper, the orientation estimation is expressed and solved in the terms of a regression problem and supervised learning. In our experiments, we have tested and compared 18 shape descriptors; the best one achieves a mean error of 5:24°. However, because of the intrinsic limitation mentioned above, the range of orientations is limited to 180°. Our method is easy to implement and outperforms existing techniques.
INTELSIG
Researchers ; Professionals ; General public
http://hdl.handle.net/2268/101285
http://www.ulg.ac.be/telecom/orientation
See the MakeHuman wikipedia page: http://en.wikipedia.org/wiki/MakeHuman

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