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Focus-of-Attention from Local Color Symmetries
July 2004 (vol. 26 no. 7)
pp. 817-830

Abstract—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.

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Index Terms:
Focus-of-attention, color vision, symmetry, saliency maps, object recognition.
Citation:
Gunther Heidemann, "Focus-of-Attention from Local Color Symmetries," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 7, pp. 817-830, July 2004, doi:10.1109/TPAMI.2004.29
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