Paper Info
Title
Two-View Orthographic Epipolar Geometry: Minimal and Optimal Solvers.
Abstract
We will in this paper present methods and algorithms for estimating two-view geometry based on an orthographic camera model. We use a previously neglected nonlinear criterion on rigidity to estimate the calibrated essential matrix. We give efficient algorithms for estimating it minimally (using only three point correspondences), in a least squares sense (using four or more point correspondences), and optimally with respect to the number of inliers. The inlier-optimal algorithm is based on a three-point solver and gives a fourth-order polynomial time algorithm. These methods can be used as building blocks to robustly find inlier correspondences in the presence of high degrees of outliers. We show experimentally that our methods can be used in many instances, where the orthographic camera model isn’t generally used. A case of special interest is situations with repetitive structures, which give high amounts of outliers in the initial feature point matching.
Year
DOI
Venue
2018
https://doi.org/10.1007/s10851-017-0753-1
Journal of Mathematical Imaging and Vision
Field
DocType
Volume
Least squares,Computer vision,Mathematical optimization,Essential matrix,Orthographic projection,Epipolar geometry,Computational mathematics,Outlier,Artificial intelligence,Solver,Time complexity,Mathematics
Journal
60
Issue
ISSN
Citations 
2
0924-9907
0
PageRank 
References 
Authors
0.34
10
1
Name
Order
Citations
PageRank
Magnus Oskarsson119622.85