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
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;
Conference_Titel :
Audio, Language and Image Processing (ICALIP), 2014 International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4799-3902-2
DOI :
10.1109/ICALIP.2014.7009909