NDLI: An efficient refinement for relative pose estimation with unknown focal length from two views

Content Provider	IEEE Xplore Digital Library
Author	Xiangguo Fu Xiaolin Zhang
Copyright Year	2012
Description	Author affiliation: Department of Information Processing, Tokyo Institute of Technology, Japan (Xiangguo Fu) \|\| Precision and Intelligence Laboratory, Tokyo Institute of Technology, Japan (Xiaolin Zhang)
Abstract	This paper describes the relative pose estimation problems in a semi-calibrated case. It is well known that the fundamental matrix completely encapsulates the epipolar geometry between two perspective views. Through the parameterization of the fundamental matrix with the minimal parameters of pose and focal length, we formulate the problem as the minimum cost estimation problem with the aid of the principle of maximum likelihood. The corresponding analytical differentiation and optimization algorithm are proposed as means for efficient computation. Experiments on simulated and real data show that the accuracy of this approach is more or less comparable to bundle adjustment and its implementation performs much better in terms of computational cost.
Starting Page	757
Ending Page	768
File Size	2712919
Page Count	12
File Format	PDF
ISBN	9781467303859
ISSN	21533598
e-ISBN	9781467303873
DOI	10.1109/PLANS.2012.6236953
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-04-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cameras Optimization Jacobian matrices Levenberg-Marquardt algorithm Pose Estimation Fundamental Matrix Maximum Likelihood Minimal Parameterization Bundle Adjustment
Content Type	Text
Resource Type	Article

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