Practical and Efficient Multi-View Matching

Eleonora Maset, Federica Arrigoni, Andrea Fusiello; The IEEE International Conference on Computer Vision (ICCV), 2017, pp. 4568-4576

Abstract


In this paper we propose a novel solution to the multi-view matching problem that, given a set of noisy pairwise correspondences, jointly updates them so as to maximize their consistency. Our method is based on a spectral decomposition, resulting in a closed-form efficient algorithm, in contrast to other iterative techniques that can be found in the literature. Experiments on both synthetic and real datasets show that our method achieves comparable or superior accuracy to state-of-the-art algorithms in significantly less time. We also demonstrate that our solution can efficiently handle datasets of hundreds of images, which is unprecedented in the literature.

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[bibtex]
@InProceedings{Maset_2017_ICCV,
author = {Maset, Eleonora and Arrigoni, Federica and Fusiello, Andrea},
title = {Practical and Efficient Multi-View Matching},
booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
month = {Oct},
year = {2017}
}