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Type: Conference paper
Title: Guaranteed outlier removal for rotation search
Author: Bustos, A.
Chin, T.
Citation: Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015 / vol.2015 International Conference on Computer Vision, ICCV 2015, pp.2165-2173
Publisher: IEEE
Issue Date: 2015
ISBN: 9781467383912
ISSN: 1550-5499
Conference Name: 2015 IEEE International Conference on Computer Vision (ICCV 2015) (07 Dec 2015 - 13 Dec 2015 : Santiago, Chile)
Statement of
Álvaro Parra Bustos, Tat-Jun Chin
Abstract: Rotation search has become a core routine for solving many computer vision problems. The aim is to rotationally align two input point sets with correspondences. Recently, there is significant interest in developing globally optimal rotation search algorithms. A notable weakness of global algorithms, however, is their relatively high computational cost, especially on large problem sizes and data with a high proportion of outliers. In this paper, we propose a novel outlier removal technique for rotation search. Our method guarantees that any correspondence it discards as an outlier does not exist in the inlier set of the globally optimal rotation for the original data. Based on simple geometric operations, our algorithm is deterministic and fast. Used as a preprocessor to prune a large portion of the outliers from the input data, our method enables substantial speed-up of rotation search algorithms without compromising global optimality. We demonstrate the efficacy of our method in various synthetic and real data experiments.
Keywords: Upper bound, search problems, three-dimensional displays, uncertainty
Rights: © 2015 IEEE
RMID: 0030056386
DOI: 10.1109/ICCV.2015.250
Appears in Collections:Computer Science publications

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