Wide-baseline multiple-view correspondences

  • Authors:

  • Vittorio Ferrari;Tinne Tuytelaars;Luc Van Gool

  • Affiliations:

  • Computer Vision Group, BIWI, ETH Zuerich, Switzerland;ESAT-PSI, University of Leuven, Belgium;Computer Vision Group, BIWI, ETH Zuerich, Switzerland and ESAT-PSI, University of Leuven, Belgium

  • Venue:
  • CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
  • Year:
  • 2003

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Abstract

We present a novel approach for establishing multiple-view feature correspondences along an unordered set of images taken from substantially different viewpoints. While recently several wide-baseline stereo (WBS) algorithms have appeared, the N-view case is largely unexplored. In this paper, an established WBS algorithm is used to extract and match features in pairs of views. The pairwise matches are first integrated into disjoint feature tracks, each representing a single physical surface patch in several views. By exploiting the interplay between the tracks, they are extended over more views, while unrelated image features are removed. Similarity and spatial relationships between the features are simultaneously used. The output consists of many reliable and accurate feature tracks, strongly connecting the input views. Applications include 3D reconstruction and object recognition. The proposed approach is not restricted to the particular choice of features and matching criteria. It can extend any method that provides feature correspondences between pairs of images.