Coherent image selection using a fast approximation to the generalized traveling salesman problem

  • Authors:
  • Meng Wang;Prakash Ishwar;Janusz Konrad;Cenk Gazen;Rohit Saboo

  • Affiliations:
  • Boston University, Boston, MA, USA;Boston University, Boston, MA, USA;Boston University, BOSTON, MA, USA;Google Inc., Mountain View, CA, USA;Google Inc., Mountain View, CA, USA

  • Venue:
  • Proceedings of the 20th ACM international conference on Multimedia
  • Year:
  • 2012

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Abstract

Searching for images on-line using keywords returns results that are often difficult to interpret. This becomes even more complicated if one attempts to compare image search output for several keywords with a common theme. We focus on the latter problem and propose a method to efficiently compare sets of images in order to find representative images, one from each set, that are coherent in certain sense. However, the search for an optimal set of representative images is very complex even for as few as 10 sets of 20 images each since all possible combinations of 10 images need to be considered. Therefore, we formulate our problem as the Generalized Traveling Salesman Problem (GTSP) and propose an efficient approximation algorithm to solve it. Our approximate GTSP algorithm is faster than other well-known approximations and is also more likely to reach the exact solution for large-scale inputs. We present a number of experimental results using the proposed algorithm and conclude that it can be a useful, almost real-time tool for on-line search.