Abstract
In order to improve the speed of surface reconstruction from densely scattered points, and reduce the application cost, this paper describes a new and fast surface reconstruction method based on grid computing. The proposed method converts large-scale unorganized 3D scanned datasets into layered datasets firstly. Then based on data parallel mechanism, a loosely coupled parallel reconstruction algorithm is designed; the algorithm has less inter-node communication, so that it is more suitable for grid computing. In order to realize load balance in grid, the priority preemptive scheduling strategy is designed based on two-level scheduling model. Finally, the grid environment is built by Globus Toolkit, and the parallel reconstruction and visualization are achieved based on mpich-G2 and the Visualization Toolkit (VTK), this experiment shows that the reconstruction time is reduced significantly.
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Feng, J., Kong, L., Wang, X. (2010). Surface Reconstruction Technology from Dense Scattered Points Based on Grid. In: Zhang, W., Chen, Z., Douglas, C.C., Tong, W. (eds) High Performance Computing and Applications. Lecture Notes in Computer Science, vol 5938. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11842-5_19
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DOI: https://doi.org/10.1007/978-3-642-11842-5_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11841-8
Online ISBN: 978-3-642-11842-5
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