A New Selective Confidence Measure---Based Approach for Stereo Matching

Authors:
Nizar Fakhfakh;Louahdi Khoudour;El-Miloudi El-Koursi;Jacques Jacot;Alain Dufaux
Affiliations:
French National Institute for Transport and Safety Research (INRETS), Villeneuve d'Ascq, France 59666 and Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland CH-1015;French National Institute for Transport and Safety Research (INRETS), Villeneuve d'Ascq, France 59666;French National Institute for Transport and Safety Research (INRETS), Villeneuve d'Ascq, France 59666;Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland CH-1015;Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland CH-1015
Venue:
KES '09 Proceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems: Part I
Year:
2009

Citing 6
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Abstract

Achieving an accurate disparity map in a reasonable processing time is a real challenge in the stereovision field. For this purpose, we propose in this paper an original approach which aims to accelerate matching time while keeping a very good matching accuracy. The proposed method allows us to shift from a dense to a sparse disparity map. Firstly, we have computed scores for all pairs of pixels using a new dissimilarity function recently developed. Then, by applying a confidence measure on each pair of pixels, we keep only couples of pixels having a high confidence measure which is computed relying on a set of new local parameters.