Focus-of-attention from local color symmetries.
In this paper, a continuous valued measure for local color symmetry is introduced. The new algorithm is an extension of the successful gray value-based symmetry map proposed by Reisfeld et al. The use of color facilitates the detection of focus points (FPs) on objects that are difficult to detect using gray-value contrast only. The detection of FPs is aimed at guiding the attention of an object recognition system; therefore, FPs have to fulfill three major requirements: stability, distinctiveness, and usability. The proposed algorithm is evaluated for these criteria and compared with the gray value-based symmetry measure and two other methods from the literature. Stability is tested against noise, object rotation, and variations of lighting. As a measure for the distinctiveness of FPs, the principal components of FP-centered windows are compared with those of windows at randomly chosen points on a large database of natural images. Finally, usability is evaluated in the context of an object recognition task.
Heidemann
Gunther
G
Faculty of Technology, Neuroinformatics Group, University of Bielefeld, PO Box 100131, Germany. gheidema@techfak.uni-bielefeld.de
D000465:Algorithms; D001185:Artificial Intelligence; D001288:Attention; D032701:Biomimetics / Q000379:methods; D003116:Color; D003124:Colorimetry / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D014796:Visual Perception