Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

10-2016

Abstract

A perennial problem in recovering 3-D models from images is repeated structures common in modern cities. The problem can be traced to the feature matcher which needs to match less distinctive features (permitting wide-baselines and avoiding broken sequences), while simultaneously avoiding incorrect matching of ambiguous repeated features. To meet this need, we develop RepMatch, an epipolar guided (assumes predominately camera motion) feature matcher that accommodates both wide-baselines and repeated structures. RepMatch is based on using RANSAC to guide the training of match consistency curves for differentiating true and false matches. By considering the set of all nearest-neighbor matches, RepMatch can procure very large numbers of matches over wide baselines. This in turn lends stability to pose estimation. RepMatch’s performance compares favorably on standard datasets and enables more complete reconstructions of modern architectures.

Keywords

Correspondence; RANSAC; Structure from motion

Discipline

Computer and Systems Architecture | Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

Proceedings of the 14th European Conference, Computer Vision - ECCV 2016, Amsterdam, October 11-14

Volume

9905

First Page

562

Last Page

597

ISBN

9783319464473

Identifier

10.1007/978-3-319-46448-0_34

Publisher

Springer Verlag

City or Country

Amsterdam

Additional URL

https://doi.org/10.1007/978-3-319-46448-0_34

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