Wide-baseline multiple-view correspondences

V. Ferrari, T. Tuytelaars, Luc Val Gool

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

We present a novel approach for establishing multiple-view feature correspondences along an unordered set of images taken from substantially different viewpoints. 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.
Original languageEnglish
Title of host publicationComputer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages8
ISBN (Print)0-7695-1900-8
Publication statusPublished - 1 Jun 2003


Dive into the research topics of 'Wide-baseline multiple-view correspondences'. Together they form a unique fingerprint.

Cite this