The space of essential matrices as a Riemannian quotient manifold
Files
Accepted manuscript
Date
2017-08-31
Authors
Tron, Roberto
Daniilidis, Kostas
Version
OA Version
Citation
R Tron, K Daniilidis. (2017) "The Space of Essential Matrices as a Riemannian Quotient Manifold." SIAM Journal on Imaging Sciences, 10(3), DOI: 10.1137/16M1091332
Abstract
The essential matrix, which encodes the epipolar constraint between points in two projective views,
is a cornerstone of modern computer vision. Previous works have proposed different characterizations
of the space of essential matrices as a Riemannian manifold. However, they either do not consider the
symmetric role played by the two views, or do not fully take into account the geometric peculiarities
of the epipolar constraint. We address these limitations with a characterization as a quotient manifold
which can be easily interpreted in terms of camera poses. While our main focus in on theoretical
aspects, we include applications to optimization problems in computer vision.
Description
License
Publisher's own licence