DocumentCode :
535270
Title :
The registration of scattered point clouds with Gauss-Markoff model
Author :
Jie Lu ; Xiaoyun Li ; Guohong Liu
Author_Institution :
Dept. of Inf. Sci., Jiangxi Vocational Technol. Coll. of Ind. & Trade, Nanchang, China
Volume :
6
fYear :
2010
fDate :
16-18 Oct. 2010
Firstpage :
2705
Lastpage :
2708
Abstract :
For large or complex objects, they have to be scanned many times to recover its entire 3D shape in reverse engineering applications. The object surface can be sampled point by point using a structure light fringe projection. The method of least squares can match overlapping surfaces to estimate rotation matrix and translating vector between a local coordinate system and the template coordinate system. The Gauss-Markoff model can minimize the sum of squares of Euclidean distances between surfaces for matching 3D surface patches. This research uses the least squares method to the Gauss-Markoff model for the registration of point clouds. A vase registration example shows the feasibility of the proposed method. It takes about 4 seconds for the registration of 1531209 points with 0.027mm registration error. The surface profile after the registration is complete and smooth, which can meet the requirement of subsequent surface reconstruction.
Keywords :
image matching; image registration; least squares approximations; 3D surface patch matching; Euclidean distance; Gauss-Markoff model; least squares method; local coordinate system; scattered point cloud registration; structure light fringe projection; template coordinate system; Clouds; Image reconstruction; Least squares approximation; Shape; Surface reconstruction; Three dimensional displays; Transmission line matrix methods; Gauss-Markoff Model; fringe projection; point clouds registration; registration error; reverse engineering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing (CISP), 2010 3rd International Congress on
Conference_Location :
Yantai
Print_ISBN :
978-1-4244-6513-2
Type :
conf
DOI :
10.1109/CISP.2010.5647472
Filename :
5647472
Link To Document :
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