Name
Title | ||
|---|---|---|
Distributed sparse bundle adjustment algorithm based on three-dimensional point partition and asynchronous communication. |
Abstract | ||
|---|---|---|
Sparse bundle adjustment (SBA) is a key but time- and memory-consuming step in three-dimensional (3D) reconstruction. In this paper, we propose a 3D point-based distributed SBA algorithm (DSBA) to improve the speed and scalability of SBA. The algorithm uses an asynchronously distributed sparse bundle adjustment (A-DSBA) to overlap data communication with equation computation. Compared with the synchronous DSBA mechanism (SDSBA), A-DSBA reduces the running time by 46%. The experimental results on several 3D reconstruction datasets reveal that our distributed algorithm running on eight nodes is up to five times faster than that of the stand-alone parallel SBA. Furthermore, the speedup of the proposed algorithm (running on eight nodes with 48 cores) is up to 41 times that of the serial SBA (running on a single node). |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1631/FITEE.1800173 | Frontiers of IT & EE |
Keywords | Field | DocType |
Sparse bundle adjustment, Parallel, Distributed sparse bundle adjustment, Three-dimensional reconstruction, Asynchronous, TP312, TP217.4 | Asynchronous communication,Computer science,Bundle adjustment,Algorithm,Distributed algorithm,Partition (number theory),3D reconstruction,Speedup,Computation,Scalability | Journal |
Volume | Issue | ISSN |
19 | 7 | 2095-9184 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaolong Shen | 1 | 2 | 2.07 |
| Yong Dou | 2 | 632 | 89.67 |
| Steven Mills | 3 | 41 | 17.74 |
| David M. Eyers | 4 | 477 | 45.90 |
| huan feng | 5 | 45 | 4.43 |
| Zhiyi Huang | 6 | 83 | 11.28 |