Distributed sparse bundle adjustment algorithm based on three-dimensional point partition and asynchronous communication

作者：Shen, Xiao-long^*; Dou, Yong; Mills, Steven; Eyers, David M.; Feng, Huan; Huang, Zhiyi

来源：Frontiers of Information Technology & Electronic Engineering, 2018, 19(7): 889-904.

DOI：10.1631/FITEE.1800173

• Sparse bundle adjustment
• Parallel
• Distributed sparse bundle adjustment
• Three-dimensional reconstruction
• Asynchronous

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).

• 出版日期2018-7
• 单位清华大学; 中国人民解放军国防科学技术大学