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Rotation Averaging

delete2013-01-30
delete413
PRE
AI
R
Richard Hartley *
J
Jochen Trumpf
Y
Yuchao Dai
H
Hongdong Li
DOI:10.1007/s11263-012-0601-0delete
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Abstract

Abstract

En 中文
This paper is conceived as a tutorial on rotation averaging, summarizing the research that has been carried out in this area; it discusses methods for single-view and multiple-view rotation averaging, as well as providing proofs of convergence and convexity in many cases. However, at the same time it contains many new results, which were developed to fill gaps in knowledge, answering fundamental questions such as radius of convergence of the algorithms, and existence of local minima. These matters, or even proofs of correctness have in many cases not been considered in the Computer Vision literature. We consider three main problems: single rotation averaging, in which a single rotation is computed starting from several measurements; multiple-rotation averaging, in which absolute orientations are computed from several relative orientation measurements; and conjugate rotation averaging, which relates a pair of coordinate frames. This last is related to the hand-eye coordination problem and to multiple-camera calibration.
Keywords:
Geodesic distance
Angular distance
Chordal distance
Quaternion distance
L-1 mean
L-2 mean
conjugate rotation
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

International Journal of Computer Vision cover
International Journal of Computer Vision
IF:
9.3
Papers:
3.9K
Citations:
2.8W

Organization

A
Australian National University
Scholars:
2.1W
Papers: 2.3W
Citations: 3.9W
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