DocumentCode
1798817
Title
A pipeline for surface reconstruction of 3-dimentional point cloud
Author
Qingtong Xu ; Jing Wang ; Xuandong An
Author_Institution
Sch. of Commun. & Inf. Eng., Shanghai Univ., Shanghai, China
fYear
2014
fDate
7-9 July 2014
Firstpage
822
Lastpage
826
Abstract
This paper achieves optimal 3D point cloud reconstruction based on the specific experiment and concrete actions, and the reconstruction results realistically reflect the real object. We introduce a pipeline for surface reconstruction, including K-nearest neighbor method for point cloud data de-noising, Poisson-disk sampling to simplify the point cloud data, k-nearest neighbor method for normal estimation and Poisson reconstruction to achieve triangular mesh reconstruction of the point cloud data. In the specific operation, we apply an algorithm and select the suitable parameters through our experience at each step, so as to achieve optimal reconstruction results.
Keywords
image denoising; image reconstruction; image sampling; stochastic processes; surface reconstruction; 3-dimensional point cloud; Poisson reconstruction; Poisson-disk sampling; k-nearest neighbor method; normal estimation; optimal 3D point cloud reconstruction; pipeline; point cloud data denoising; surface reconstruction; triangular mesh reconstruction; Image reconstruction; Noise; Noise reduction; Solid modeling; Surface reconstruction; Surface treatment; Three-dimensional displays; Poisson reconstruction; Poisson-disk sampling; de-noising; normal estimation; pipeline;
fLanguage
English
Publisher
ieee
Conference_Titel
Audio, Language and Image Processing (ICALIP), 2014 International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4799-3902-2
Type
conf
DOI
10.1109/ICALIP.2014.7009909
Filename
7009909
Link To Document