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Gesture recognition in flow based on PCA analysis using multiagent system
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ACM International Conference Proceeding Series; Vol. 352 archive
Proceedings of the 2008 International Conference on Advances in Computer Entertainment Technology table of contents
Yokohama, Japan
SESSION: Technical track: Interface table of contents
Pages: 139-146  
Year of Publication: 2008
ISBN:978-1-60558-393-8
Authors
Ronan Billon  Centre Européen de Réalité, Virtuelle, Plouzané, France
Alexis Nédélec  Centre Européen de Réalité, Virtuelle, Plouzané, France
Jacques Tisseau  Centre Européen de Réalité, Virtuelle, Plouzané, France
Sponsors
IPSJ : Information Processing Society of Japan
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
Publisher
ACM  New York, NY, USA
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ABSTRACT

Our context is Virtual Theater. Our aim is to put on a short play featuring a real actor and a virtual actor, who will communicate through movements and choreography with mutual synchronization. We currently work on a system that can recognize key-gestures made by a real actor.

In this paper, we cover a method for real-time recognition. Our idea is that the data for movements from any motion-capture system can be reduced to a single artificial signature. We use properties from Principal Component Analysis (PCA) to generate it. This artificial gesture representation is used in real-time by our multiagent systems to simultaneously perform segmentation (gesture's beginning and end) and recognition. We conducted various experiments which demonstrate our system and define its limitations.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
M. Aubry, F. Julliard, and S. Gibet. Apprentissage des paramètres d'un contrôleur pour la synthèse de mouvements réalistes. Journées l'Aber Wrac'h des 29 et 30 mai 2008, Jun 2008.
 
2
 
3
 
4
 
5
S. Boukir and F. Cheneviere. Conception d'un systÃĺme de reconnaissance de gestes dansés = design of a dance gesture recognition system. TS. Traitement du signal (Trait. signal) ISSN 0765-0019, 21(3):195--203, 2004.
 
6
7
 
8
9
 
10
11
 
12
 
13
 
14
N. Magnenat-Thalmann and A. Egges. Interactive virtual humans in real-time virtual environments. The International Journal of Virtual Reality, 5(2):15--24, June 2006.
 
15
N. Rezzoug, P. Gorce, A. Heloir, S. Gibet, N. Courty, J.-F. Kamp, F. Multon, and C. Pelachaud. Virtual humanoids endowed with expressive communication gestures: the hugex project. In Proc. of IEEE Systems, Man and Cybernetics, Taipei, Taiwan, October 2006. IEEE CS.
 
16
 
17
A. Sandberg. Gesture recognition using neural networks, 1997. Master's thesis TRITA-NA-E9727, dept.
 
18
J. Shlens. A tutorial on principal component analysis, December 2005.
 
19
 
20
 
21
J. Yamato, J. Ohya, and K. Ishii. Recognizing human action in time-sequential images using hidden markov model. Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on, pages 379--385, 15--18 Jun 1992.
 
22
H. Zhou and H. Hu. A survey--human movement tracking and stroke rehabilitation, 2004. Technical Report: CSM-420.

Collaborative Colleagues:
Ronan Billon: colleagues
Alexis Nédélec: colleagues
Jacques Tisseau: colleagues