Hierarchical graphics databases in sort-first
PRS '97 Proceedings of the IEEE symposium on Parallel rendering
The digital Michelangelo project: 3D scanning of large statues
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Delaunay based shape reconstruction from large data
PVG '01 Proceedings of the IEEE 2001 symposium on parallel and large-data visualization and graphics
Smooth surface reconstruction from noisy range data
Proceedings of the 1st international conference on Computer graphics and interactive techniques in Australasia and South East Asia
The Ball-Pivoting Algorithm for Surface Reconstruction
IEEE Transactions on Visualization and Computer Graphics
Interpolation and Approximation of Surfaces from Three-dimensional Scattered Data Points
Dagstuhl '97, Scientific Visualization
Using Growing Cell Structures for Surface Reconstruction
SMI '03 Proceedings of the Shape Modeling International 2003
Shared virtual memory on loosely coupled multiprocessors
Shared virtual memory on loosely coupled multiprocessors
Improving the performance of shared virtual memory on system area networks
Improving the performance of shared virtual memory on system area networks
Improvements to surface reconstruction by the CRUST algorithm
SCCG '03 Proceedings of the 19th spring conference on Computer graphics
A system for reconstruction of solid models from large point clouds
Machine Graphics & Vision International Journal
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Surface reconstruction is a common problem in computer graphics. Given a set of points sampled from some surface, a triangle mesh interpolating or approximating the points is to be obtained. One of very often used techniques for solving this problem is the selection of surface triangles from the set of Delaunay tetrahedronization faces. In the case of large data, it is difficult to obtain the tetrahedronization due to its huge memory requirements. One of possible solutions is to use distributed computing. Here, we describe the newly developed VSM (Virtual Shared Memory) distributed toolkit and its utilization for the task of surface reconstruction. By our approach, we were able to process dataset having 1.4M points on 4xP4 interconnected via 100Mb Ethernet in 6 hours. About 5GB of memory was consumed during the reconstruction.