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A Turbo-Inspired Iterative Approach for Correspondence Problems of Image Features

A. Aboudib, V. Gripon and G. Coppin, "A Turbo-Inspired Iterative Approach for Correspondence Problems of Image Features," in Proceedings of the 9th International Symposium on Turbo Codes and Iterative Information Processing, pp. 226--230, September 2016.

Establishing correspondences between image features is a fundamental problem in many computer vision tasks. It is traditionally viewed as a graph matching problem, and solved using an optimization procedure. In this paper, we propose a new approach to solving the correspondence problem from a coding/decoding perspective. We then present an iterative matching algorithm inspired from the turbo-decoding concept. We provide an experimental evaluation of the proposed method, and show that it performs better than state-of-the-art algorithms in the presence of clutter, thanks to turbo-style decoding.

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Bibtex
@inproceedings{AboGriCop20169,
  author = {Ala Aboudib and Vincent Gripon and Gilles
Coppin},
  title = {A Turbo-Inspired Iterative Approach for
Correspondence Problems of Image Features},
  booktitle = {Proceedings of the 9th International
Symposium on Turbo Codes and Iterative Information
Processing},
  year = {2016},
  pages = {226--230},
  month = {September},
}




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