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Partial Similarity of Objects, or How to Compare a Centaur to a Horse

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Abstract

Similarity is one of the most important abstract concepts in human perception of the world. In computer vision, numerous applications deal with comparing objects observed in a scene with some a priori known patterns. Often, it happens that while two objects are not similar, they have large similar parts, that is, they are partially similar. Here, we present a novel approach to quantify partial similarity using the notion of Pareto optimality. We exemplify our approach on the problems of recognizing non-rigid geometric objects, images, and analyzing text sequences.

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Authors and Affiliations

  1. Department of Computer Science, Technion—Israel Institute of Technology, Haifa, 32000, Israel

    Alexander M. Bronstein, Michael M. Bronstein, Alfred M. Bruckstein & Ron Kimmel

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  1. Alexander M. Bronstein
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  2. Michael M. Bronstein
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  3. Alfred M. Bruckstein
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  4. Ron Kimmel
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Correspondence to Alexander M. Bronstein.

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Bronstein, A.M., Bronstein, M.M., Bruckstein, A.M. et al. Partial Similarity of Objects, or How to Compare a Centaur to a Horse. Int J Comput Vis 84, 163–183 (2009). https://doi.org/10.1007/s11263-008-0147-3

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