Power Bundle Adjustment for Large-Scale 3D Reconstruction
- URL: http://arxiv.org/abs/2204.12834v4
- Date: Mon, 17 Apr 2023 13:52:06 GMT
- Title: Power Bundle Adjustment for Large-Scale 3D Reconstruction
- Authors: Simon Weber and Nikolaus Demmel and Tin Chon Chan and Daniel Cremers
- Abstract summary: We introduce Power Bundle Adjustment as an expansion type algorithm for solving large-scale bundle adjustment problems.
It is based on the power series expansion of the inverse Schur complement and constitutes a new family of solvers that we call inverse expansion methods.
- Score: 47.08614319083826
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We introduce Power Bundle Adjustment as an expansion type algorithm for
solving large-scale bundle adjustment problems. It is based on the power series
expansion of the inverse Schur complement and constitutes a new family of
solvers that we call inverse expansion methods. We theoretically justify the
use of power series and we prove the convergence of our approach. Using the
real-world BAL dataset we show that the proposed solver challenges the
state-of-the-art iterative methods and significantly accelerates the solution
of the normal equation, even for reaching a very high accuracy. This
easy-to-implement solver can also complement a recently presented distributed
bundle adjustment framework. We demonstrate that employing the proposed Power
Bundle Adjustment as a sub-problem solver significantly improves speed and
accuracy of the distributed optimization.
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