Critical Parameter Consensus for Efficient Distributed Bundle Adjustment

Zhuohao Liu, Changyu Diao, Wei Xing, Dongming Lu

2019

Abstract

We present a critical parameter consensus framework to improve the efficiency of Distributed Bundle Adjustment (DBA). Existing DBA methods are based solely on either camera consensus or point consensus, often resulting in excessive local computation time or large data transmission overhead. To address this issue, we jointly partition points and cameras, and perform the consensus on both overlapping cameras and points. Our joint block partitioning method first initializes a non-overlapping block partition, maximizing local problem constraints and ensuring a uniform partition. Then overlapping cameras and points are added in a greedy manner to maximize the partition score that quantifies the efficiency of DBA for local blocks. Experimental results on public datasets show that we can achieve better computational efficiency without loss of accuracy.

Paper Citation

in Harvard Style

Liu Z., Diao C., Xing W. and Lu D. (2019). Critical Parameter Consensus for Efficient Distributed Bundle Adjustment. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP; ISBN 978-989-758-354-4, SciTePress, pages 800-807. DOI: 10.5220/0007361108000807

in Bibtex Style

@conference{visapp19,
author={Zhuohao Liu and Changyu Diao and Wei Xing and Dongming Lu},
title={Critical Parameter Consensus for Efficient Distributed Bundle Adjustment},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP},
year={2019},
pages={800-807},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007361108000807},
isbn={978-989-758-354-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP
TI - Critical Parameter Consensus for Efficient Distributed Bundle Adjustment
SN - 978-989-758-354-4
AU - Liu Z.
AU - Diao C.
AU - Xing W.
AU - Lu D.
PY - 2019
SP - 800
EP - 807
DO - 10.5220/0007361108000807
PB - SciTePress