Distributed sparse bundle adjustment algorithm based on three-dimensional point partition and asynchronouscommunication
Xiao-long SHEN , Yong DOU , Steven MILLS , David M EYERS , Huan FENG , Zhiyi HUANG
Front. Inform. Technol. Electron. Eng ›› 2018, Vol. 19 ›› Issue (7) : 889 -904.
Distributed sparse bundle adjustment algorithm based on three-dimensional point partition and asynchronouscommunication
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).
Sparse bundle adjustment / Parallel / Distributed sparse bundle adjustment / Three-dimensional reconstruction / Asynchronous
Zhejiang University and Springer-Verlag GmbH Germany, part of Springer Nature
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