Next Article in Journal
A Hybrid Method for Optimal Siting and Sizing of Battery Energy Storage Systems in Unbalanced Low Voltage Microgrids
Previous Article in Journal
Development of a High-Fidelity Model for an Electrically Driven Energy Storage Flywheel Suitable for Small Scale Residential Applications
Open AccessArticle

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

by Xianglin Meng 1,*, Wantao He 2,* and Junyan Liu 3
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.
Appl. Sci. 2018, 8(3), 454; https://doi.org/10.3390/app8030454
Received: 5 February 2018 / Revised: 12 March 2018 / Accepted: 14 March 2018 / Published: 16 March 2018
(This article belongs to the Section Mechanical Engineering)
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
Show Figures

Figure 1

MDPI and ACS Style

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.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop