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

  • Authors:
  • Alexander M. Bronstein;Michael M. Bronstein;Alfred M. Bruckstein;Ron Kimmel

  • Affiliations:
  • Department of Computer Science, Technion--Israel Institute of Technology, Haifa, Israel 32000;Department of Computer Science, Technion--Israel Institute of Technology, Haifa, Israel 32000;Department of Computer Science, Technion--Israel Institute of Technology, Haifa, Israel 32000;Department of Computer Science, Technion--Israel Institute of Technology, Haifa, Israel 32000

  • Venue:
  • International Journal of Computer Vision
  • Year:
  • 2009

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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.