A Dipolar Competitive Neural Network for Video Segmentation

Authors:
R. M. Luque;D. López-Rodríguez;E. Dominguez;E. J. Palomo
Affiliations:
Department of Computer Science, University of Málaga, Málaga, Spain;Department of Applied Mathematics, University of Málaga, Málaga, Spain;Department of Computer Science, University of Málaga, Málaga, Spain;Department of Computer Science, University of Málaga, Málaga, Spain
Venue:
IBERAMIA '08 Proceedings of the 11th Ibero-American conference on AI: Advances in Artificial Intelligence
Year:
2008

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Abstract

This paper present a video segmentation method which separate pixels corresponding to foreground from those corresponding to background. The proposed background model consists of a competitive neural network based on dipoles, which is used to classify the pixels as background or foreground. Using this kind of neural networks permits an easy hardware implementation to achieve a real time processing with good results. The dipolar representation is designed to deal with the problem of estimating the directionality of data. Experimental results are provided by using the standard PETS dataset and compared with the mixture of Gaussians and background subtraction methods.