Robust Relative Rotation Averaging

Chatterjee, Avishek and Govindu, Venu Madhav (2018) Robust Relative Rotation Averaging. In: IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 40 (4). pp. 958-972.

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Abstract

This paper addresses the problem of robust and efficient relative rotation averaging in the context of large-scale Structure from Motion. Relative rotation averaging finds global or absolute rotations for a set of cameras from a set of observed relative rotations between pairs of cameras. We propose a generalized framework of relative rotation averaging that can use different robust loss functions and jointly optimizes for all the unknown camera rotations. Our method uses a quasi-Newton optimization which results in an efficient iteratively reweighted least squares (IRLS) formulation that works in the Lie algebra of the 3D rotation group. We demonstrate the performance of our approach on a number of large-scale data sets. We show that our method outperforms existing methods in the literature both in terms of speed and accuracy.

Item Type:	Journal Article
Publication:	IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
Publisher:	IEEE COMPUTER SOC, 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314 USA
Additional Information:	Copy right for the article belong to IEEE COMPUTER SOC, 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314 USA
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	02 Apr 2018 19:58
Last Modified:	02 Apr 2018 19:58
URI:	http://eprints.iisc.ac.in/id/eprint/59435

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