DocumentCode :
592970
Title :
Normal Vector of the 3D Point Cloud Estimates and Close to the Point Normal Vector Adjustment Methods
Author :
Jie Xu ; Jun Xu ; Xiao-yang Yu
Author_Institution :
Heilongjiang Inst. of Sci. & Technol., Harbin, China
fYear :
2012
fDate :
8-10 Dec. 2012
Firstpage :
610
Lastpage :
613
Abstract :
The normal vector is one of the important properties of the 3D point cloud data, estimation methods have been important research in the field. The normal vector estimation is the basis of the 3D point cloud subsequent follow-up of the light treatment, curvature calculation and surface reconstruction. Introduced an automatic space by greatly increasing the speed of the point cloud neighborhood search, given the fast and efficient point cloud normal vector estimation and adjustment algorithm based on the normal vector near the point, the experiments show the effectiveness of the method.
Keywords :
estimation theory; instruments; surface reconstruction; 3D measurement equipment; 3D point cloud data; automatic space; curvature calculation; estimation methods; light treatment; point cloud neighborhood search; point normal vector adjustment methods; surface reconstruction; Algorithm design and analysis; Estimation; Fitting; Image reconstruction; Surface reconstruction; Surface treatment; Vectors; Minimum Spanning Tree; Normal Vector; Three-dimensional point clouds; normal estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation, Measurement, Computer, Communication and Control (IMCCC), 2012 Second International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4673-5034-1
Type :
conf
DOI :
10.1109/IMCCC.2012.150
Filename :
6428983
Link To Document :
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