A region-growing algorithm using parallel computing for surface reconstruction from unorganized points

Authors: H.-T. Yau, T.-J. Yang, H.-Z. Jian

Abstract: 
A parallel computing region-growing algorithm for surface reconstruction from unorganized point clouds is proposed in this research. The traditiona l region-growing algorithm belongs to sequential process and needs to update the topology information continuously to maintain the boundaries of the growing region. This constraint becomes a bottleneck for efficiency improvement. The proposed GPU-based region-growing algorithm is to decompose the traditional sequence and re-plan specific framew ork for the purpose of utilizing parallel computation. Then, a graphics card with multi-processing units will be used to build triangles in the parallel computing mode. In our GPU-bas ed reconstructio n process, each sampling point is regarded as an independent seed and expands simultaneously until all surrou nding patches overlap each other. Following this, the overlapping patches are removed and holes are filled by the GPU-based calculation. Finally, a complete model is created. In order to validate the algorithm proposed, the unorganized point cloud was obtained by a 3D scanner and then reconstructed using the parallel computing regiongrowing algorithm. According to the results obtained, the algorithm proposed here shows 10 times better performance when compared to the traditional region-growing method.

Keywords:
GPU-based computation
Surface reconstruction
Region-growing algorithm
Candidate triangle table
Overlapping triangle removal
Filling small hole

Published in: Advances Engineering Software (Volume 59, March 2013)

Publisher: Elsevier

ISSN Information: 0965-9978

A region-growing algorithm using parallel computing for surface reconstruction from unorganized points

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