Segmentation of Moving Objects with Information Feedback Between Description Levels

Authors:
M. Rincón;E. J. Carmona;M. Bachiller;E. Folgado
Affiliations:
Dpto. de Inteligencia Artificial. ETSI Informatica. UNED., Juan del Rosal 16, 28040 Madrid, Spain;Dpto. de Inteligencia Artificial. ETSI Informatica. UNED., Juan del Rosal 16, 28040 Madrid, Spain;Dpto. de Inteligencia Artificial. ETSI Informatica. UNED., Juan del Rosal 16, 28040 Madrid, Spain;Dpto. de Inteligencia Artificial. ETSI Informatica. UNED., Juan del Rosal 16, 28040 Madrid, Spain
Venue:
IWINAC '07 Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II
Year:
2007

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Abstract

In real sequences, one of the factors that most negatively affects the segmentation process result is the existence of scene noise. This impairs object segmentation which has to be corrected if we wish to have some minimum guarantees of success in the following tracking or classification stages. In this work we propose a generic knowledge-based model to improve the segmentation process. Specifically, the model uses a decomposition strategy in description levels to enable the feedback of information between adjacent levels. Finally, two case studies are proposed that instantiate the model proposed for detecting humans.