Towards Segmentation from Multiple Cues: Symmetry and Color

Authors:
Roy Shor;Nahum Kiryati
Affiliations:
-;-
Venue:
Proceedings of the 10th International Workshop on Theoretical Foundations of Computer Vision: Multi-Image Analysis
Year:
2000

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Abstract

Towards segmentation from multiple cues, this paper demonstrates the combined use of color and symmetry for detecting regions of interest (ROI), using the detection of man-made wooden objects and the detection of faces as working examples. A functional that unifies color compatibility and color-symmetry within elliptic supports is defined. Using this functional, the ROI detection problem becomes a five-dimensional global optimization problem. Exhaustive-search is inapplicable due its prohibitive computational cost. Genetic search converges rapidly and provides good results. The added value obtained by combining color and symmetry is demonstrated.