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Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/30410
Title: Adaptive color model for figure-ground segmentation in dynamic environments
Authors: Moreno-Noguer, Francesc; Sanfeliu, Alberto
Keywords: Tracking
Deformable contours
Color adaption
Particle filters
Pattern recognition: Computer vision
Pattern recognition: Object detection
Pattern recognition systems
Computer vision
Issue Date: 2004
Publisher: Springer
Citation: 9th Iberoamerican Congress on Pattern Recognition: pp. 37-44 (2004)
Abstract: In this paper we propose a new technique to perform figure-ground segmentation in image sequences of scenarios with varying illumination conditions. Most of the algorithms in the literature that adapt color, assume smooth color changes over time. On the contrary, our technique formulates multiple hypotheses about the next state of the color distribution (modelled with a Mixture of Gaussians -MoG-), and validates them taking into account shape information of the object. The fusion of shape and color is done in a stage denominated 'sample concentration', that we introduce as a final step to the classical CONDENSATION algorithm. The multiple hypotheses generation, allows for more robust adaptions procedures, and the assumption of gradual change of the lighting conditions over time is no longer necessary.
Description: Iberoamerican Congress on Pattern Recognition (CIARP), 2004, Puebla (Mexico)
URI: http://hdl.handle.net/10261/30410
ISBN: 97835402352729
Appears in Collections:(IRII) Comunicaciones congresos
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