Surface reconstruction technology from dense scattered points based on grid

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. © 2010 Springer-Verlag.