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
Citation
LIN, Wen-yan; LIU, Siying; DO, Minh N.; TAN, Ping; and LU, Jiangbo.
Repmatch: Robust feature matching and pose for reconstructing modern cities. (2016). Proceedings of the 14th European Conference, Computer Vision - ECCV 2016, Amsterdam, October 11-14. 9905, 562-597.
Available at: https://ink.library.smu.edu.sg/sis_research/4903
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/978-3-319-46448-0_34