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.
@article{arxiv.2204.12834,
title = {Power Bundle Adjustment for Large-Scale 3D Reconstruction},
author = {Simon Weber and Nikolaus Demmel and Tin Chon Chan and Daniel Cremers},
journal= {arXiv preprint arXiv:2204.12834},
year = {2023}
}