Name
Abstract | ||
|---|---|---|
Bundle adjustment (BA) is widely used in SLAM and SfM, which are key technologies in Augmented Reality. For real-time SLAM and large-scale SfM, the efficiency of BA is of great importance. This paper proposes CoLi-BA, a novel and efficient BA solver that significantly improves the optimization speed by compact linearization and reordering. Specifically, for each reprojection function, the redundant matrix representation of Jacobian is replaced with a tiny 3D vector, by which the computational complexity, memory storage, and cache missing for Hessian matrix construction and Schur complement are significantly reduced. Besides, we also propose a novel reordering strategy to improve the cache efficiency for Schur complement. Experiments on diverse datasets show that the speed of the proposed CoLi-BA is five times that of Ceres and two times that of g2o without sacrificing accuracy. We further verify the effectiveness by porting CoLi-BA to the open-source SLAM and SfM systems. Even when running the proposed solver in a single thread, the local BA of SLAM only takes about 20ms on a desktop PC, and the reconstruction of SfM with seven thousand photos only takes half an hour. The source code is available on the webpage: https://github.com/zju3dv/CoLi-BA. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TVCG.2022.3203119 | IEEE Transactions on Visualization and Computer Graphics |
Keywords | DocType | Volume |
Bundle adjustment,Compact linearization,Schur complement,SLAM,Structure-from-Motion | Journal | 28 |
Issue | ISSN | Citations |
11 | 1077-2626 | 0 |
PageRank | References | Authors |
0.34 | 28 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhichao Ye | 1 | 0 | 1.01 |
| Guanglin Li | 2 | 0 | 0.34 |
| Haomin Liu | 3 | 62 | 4.35 |
| Zhaopeng Cui | 4 | 93 | 16.66 |
| Hujun Bao | 5 | 2801 | 174.65 |
| Guofeng Zhang | 6 | 561 | 41.50 |