A Deflation Based Fast and Robust Preconditioner for Bundle Adjustment

Shrutimoy Das, Siddhant Katyan, Pawan Kumar; Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2021, pp. 1782-1789

Abstract

The bundle adjustment(BA) problem is formulated as a non linear least squares problem, which requires the solution of a linear system. For solving this system, we present the design and implementation of a fast preconditioned solver. The proposed preconditioner is based on the deflation of the largest eigenvalues of the Hessian. We also derive an estimate of the condition number of the preconditioned system. Numerical experiments on problems from the BAL dataset suggest that our solver is the fastest, sometimes, by a factor of five, when compared to the current state-of-the-art solvers for bundle adjustment.

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[bibtex]
@InProceedings{Das_2021_WACV, author = {Das, Shrutimoy and Katyan, Siddhant and Kumar, Pawan}, title = {A Deflation Based Fast and Robust Preconditioner for Bundle Adjustment}, booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)}, month = {January}, year = {2021}, pages = {1782-1789} }