@inproceedings{5bca01eebfda44178b2bfe575779e983,
title = "Repmatch: Robust feature matching and pose for reconstructing modern cities",
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{\textquoteright}s performance compares favorably on standard datasets and enables more complete reconstructions of modern architectures.",
keywords = "Correspondence, RANSAC, Structure from motion",
author = "Lin, {Wen Yan} and Siying Liu and Nianjuan Jiang and Do, {Minh N.} and Ping Tan and Jiangbo Lu",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 14th European Conference on Computer Vision, ECCV 2016 ; Conference date: 11-10-2016 Through 14-10-2016",
year = "2016",
doi = "10.1007/978-3-319-46448-0_34",
language = "English (US)",
isbn = "9783319464473",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "562--579",
editor = "Bastian Leibe and Jiri Matas and Nicu Sebe and Max Welling",
booktitle = "Computer Vision - 14th European Conference, ECCV 2016, Proceedings",
address = "Germany",
}