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Appl. Sci. 2018, 8(3), 454; https://doi.org/10.3390/app8030454

An Investigation of the High Efficiency Estimation Approach of the Large-Scale Scattered Point Cloud Normal Vector

1
School of Mechanical Engineering, Heilongjiang University of Science and Technology, Harbin 150027, China
2
State Key Laboratory of Material Processing and Die & Mould Technology, Huazhong University of Science and Technology, Wuhan 430074, China
3
School of Mechatronic Engineering, Harbin Institute of Technology, Harbin 150001, China
*
Authors to whom correspondence should be addressed.
Received: 5 February 2018 / Revised: 12 March 2018 / Accepted: 14 March 2018 / Published: 16 March 2018
(This article belongs to the Section Mechanical Engineering)
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Abstract

The normal vector estimation of the large-scale scattered point cloud (LSSPC) plays an important role in point-based shape editing. However, the normal vector estimation for LSSPC cannot meet the great challenge of the sharp increase of the point cloud that is mainly attributed to its low computational efficiency. In this paper, a novel, fast method-based on bi-linear interpolation is reported on the normal vector estimation for LSSPC. We divide the point sets into many small cubes to speed up the local point search and construct interpolation nodes on the isosurface expressed by the point cloud. On the premise of calculating the normal vectors of these interpolated nodes, a normal vector bi-linear interpolation of the points in the cube is realized. The proposed approach has the merits of accurate, simple, and high efficiency, because the algorithm only needs to search neighbor and calculates normal vectors for interpolation nodes that are usually far less than the point cloud. The experimental results of several real and simulated point sets show that our method is over three times faster than the Elliptic Gabriel Graph-based method, and the average deviation is less than 0.01 mm. View Full-Text
Keywords: normal vector; large-scale; scattered point cloud; hash table; interpolation normal vector; large-scale; scattered point cloud; hash table; interpolation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Meng, X.; He, W.; Liu, J. An Investigation of the High Efficiency Estimation Approach of the Large-Scale Scattered Point Cloud Normal Vector. Appl. Sci. 2018, 8, 454.

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