Abstract : Many image analysis and computer vision problems can be formulated as a scene labeling problem in which each site is to be assigned a label from a discrete or continuous label set with contextual information. In this paper we present a new labeling algorithm based on game theory. More precisely, we use Markov random fields to model images, and we design an n-person cooperative game which yields a deterministic optimization algorithm. Experimental results show that the algorithm is efficient and effective, exhibiting very fast convergence, and producing better results than the recently proposed non-cooperative game approach. We also compare this algorithm with other labeling algorithms on real-world and synthetic images
Type de document :
Communication dans un congrès
ICSP'98 - Fourth International Conference on Signal Processing, Oct 1998, Beijing, China. IEEE
https://hal.inria.fr/hal-01087882
Contributeur : Shan Yu
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Soumis le : jeudi 27 novembre 2014 - 04:21:52
Dernière modification le : samedi 27 janvier 2018 - 01:30:51
Guodong Guo, Shan Yu, Songde Ma. An Image Labeling Algorithm Based on Cooperative Game Theory. ICSP'98 - Fourth International Conference on Signal Processing, Oct 1998, Beijing, China. IEEE. 〈hal-01087882〉
