Ondrej Chum

TL;DR: The high utility of MSERs, multiple measurement regions and the robust metric is demonstrated in wide-baseline experiments on image pairs from both indoor and outdoor scenes.

TL;DR: The wide-baseline stereo problem, i.e. the problem of establishing correspondences between a pair of images taken from different viewpoints, is studied and an efficient and practically fast detection algorithm is presented for an affinely-invariant stable subset of extremal regions, the maximally stable extremal region (MSER).

TL;DR: To improve query performance, this work adds an efficient spatial verification stage to re-rank the results returned from the bag-of-words model and shows that this consistently improves search quality, though by less of a margin when the visual vocabulary is large.

TL;DR: In this paper, a weighted set of visual words is obtained by selecting words based on proximity in descriptor space, and this representation may be incorporated into a standard tf-idf architecture and how spatial verification is modified in the case of this soft-assignment.

TL;DR: A new robust matching method, PROSAC, which exploits the linear ordering defined on the set of correspondences by a similarity function used in establishing tentative correspondences and achieves large computational savings.