Application of Genetic Algorithm for Computing a Global 3D Scene Exploration

Oana Livia Apostu, Karim Tamine

.

DOI: 10.4236/jsea.2011.44028                

Abstract

This paper is dedicated to virtual world exploration techniques, which have to help a human being to understand a 3D scene. A new method to compute a global view of a scene is presented in the paper. The global view of a scene is determined by a “good” set off points of view. This method is based on a genetic algorithm. The “good” set of points of view is used to compute a camera path around the scene.

Keywords

Genetic Algorithm, Global Virtual World Exploration

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	E. Marchand and N. Courty, “Image-Based Virtual Camera Motion Strategies,” Graphics Interface Conference, Montreal, May 2000.
[2]	C. Colin, “A System for Exploring the Universe of Polyhedral Shapes,” Proceedings of Eurographics’88, Nice, Vol. 11, 1988.
[3]	D. Plemenos, M. Sbert and M. Feixas, “On Viewpoint Complexity of 3D Scenes,” International Conference on Computer Graphics and Vision, Moscow, September 2004.
[4]	P. P. Vazquez, M. Feixas, M. Sbert and W. Heidrich, “Viewpoint Selection Using Viewpoint Entropy,” Proceedings of the Vision Modeling and Visualization Conference, Stuttgart, 21-23 November 2001.
[5]	J. Louchet, “Using an Individual Evolution Strategy for Stereovision,” Genetic Programming and Evolvable Machines, Kluwer Academic Publishers, Vol. 2, No. 2, 2001, pp. 101-109. doi:10.1023/A:1011544128842
[6]	P. Barral, G. Dorme and D. Plemenos, “Visual Understanding of a Scene by Automatic Movement of Camera,” The 9th International Conference on Computer Graphics and Vision, Moscow, 1999.
[7]	P. Barral, G. Dorme and D. Plemenos, “Scene Understanding Using a Virtual Camera,” Eurographics’2000, Interlagen, 20-25 August 2000.
[8]	M. Feixas, “An Information Theory Framework for the Study of the Complexity of Visibility and Radiosity in a Scene,” Ph.D. Thesis, University of Catalonia, 2002.
[9]	T. Kamada and S. Kawal, “A Simple Method for Computing General Position in Displaying Three-Dimensionnal Objects,” Computer Vision, Graphics and Image Processing, Vol. 41, No. 1, 1988, pp. 43-56. doi:10.1016/0734-189X(88)90116-8
[10]	G. Turk, “Generating Random Points in a Triangle,” In: A. Glassner, Ed., Graphics Gems I, AP Professional, 1990.
[11]	H. Noser, O. Renault, D. Thalman and N. M Thalman, “Navigation for Digital Actors Based on Synthetic Vision, Memory and Vision, Memory and Learning,” Computer & Graphics, Vol. 19, No. 1, 1995, pp. 7-19. doi:10.1016/0097-8493(94)00117-H
[12]	D. Plemenos, J. Grasset, B. Jaubert and K. Tamine, “Intelligent Visibility-Based 3D Scene Processing Techniques for Computer Games,” International Conference on the Computer Graphics and Vision, Novosibirsk, June 2005, pp. 84-91.
[13]	D. Sokolov and D. Plemenos, “Viewpoint Quality and Scene Anderstanding,” The 6th International Symposium on Virtual Reality, Archaeology and Cultural, Pisa, 8-11 November 2005, pp. 173-185.
[14]	J. Louchet, M. Guyon, M. J. Lesot and A. Boumaza, “Guider un Robot Par Evolution Artificielle en Temps Réel,” Revue Extraction des Connaissances et Apprenti- ssage et évolution, Editions Hermès, December 2001, pp. 115-130.
[15]	S. Lin and B. W. Kernighan, “An Effective Heuristic Algorithm for the Traveling-Salesman Problem,” Opera- tions Research, Vol. 21, No. 1, 1973, pp. 498-516. doi:10.1287/opre.21.2.498