TY - GEN
T1 - Multidirectional Conjugate Gradients for Scalable Bundle Adjustment
AU - Weber, Simon
AU - Demmel, Nikolaus
AU - Cremers, Daniel
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - We revisit the problem of large-scale bundle adjustment and propose a technique called Multidirectional Conjugate Gradients that accelerates the solution of the normal equation by up to 61%. The key idea is that we enlarge the search space of classical preconditioned conjugate gradients to include multiple search directions. As a consequence, the resulting algorithm requires fewer iterations, leading to a significant speedup of large-scale reconstruction, in particular for denser problems where traditional approaches notoriously struggle. We provide a number of experimental ablation studies revealing the robustness to variations in the hyper-parameters and the speedup as a function of problem density.
AB - We revisit the problem of large-scale bundle adjustment and propose a technique called Multidirectional Conjugate Gradients that accelerates the solution of the normal equation by up to 61%. The key idea is that we enlarge the search space of classical preconditioned conjugate gradients to include multiple search directions. As a consequence, the resulting algorithm requires fewer iterations, leading to a significant speedup of large-scale reconstruction, in particular for denser problems where traditional approaches notoriously struggle. We provide a number of experimental ablation studies revealing the robustness to variations in the hyper-parameters and the speedup as a function of problem density.
KW - Bundle adjustment
KW - Large-scale reconstruction
KW - Preconditioned conjugate gradients
UR - http://www.scopus.com/inward/record.url?scp=85124299297&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-92659-5_46
DO - 10.1007/978-3-030-92659-5_46
M3 - Conference contribution
AN - SCOPUS:85124299297
SN - 9783030926588
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 712
EP - 724
BT - Pattern Recognition - 43rd DAGM German Conference, DAGM GCPR 2021, Proceedings
A2 - Bauckhage, Christian
A2 - Gall, Juergen
A2 - Schwing, Alexander
PB - Springer Science and Business Media Deutschland GmbH
T2 - 43rd DAGM German Conference on Pattern Recognition, DAGM GCPR 2021
Y2 - 28 September 2021 through 1 October 2021
ER -