Distributed sparse bundle adjustment algorithm based on three-dimensional point partition and asynchronous communication
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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).
Key wordsSparse bundle adjustment Parallel Distributed sparse bundle adjustment Three-dimensional reconstruction Asynchronous
CLC numberTP312 TP217.4
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- Hänsch R, Drude I, Hellwich O, 2016. Modern methods of bundle adjustment on the GPU. ISPRS Ann Photogr Remote Sens Spatial Inform Sci, III–(3):43–50. https://doi.org/10.5194/isprs-annals-III-3-43-2016 Google Scholar
- Heinecke A, Vaidyanathan K, Smelyanskiy M, et al., 2013. Design and implementation of the linpack benchmark for single and multi–node systems based on IntelR Xeon Phi coprocessor. Proc 27th Int Symp on Parallel and Distributed Processing, p.126–137. https://doi.org/10.1109/IPDPS.2013.113 Google Scholar