DocumentCode :
1605113
Title :
Surface registration by matching oriented points
Author :
Johnson, Andrew Edie ; Hebert, Martial
Author_Institution :
Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
fYear :
1997
Firstpage :
121
Lastpage :
128
Abstract :
For registration of 3-D free-form surfaces we have developed a representation which requires no knowledge of the transformation between views. The representation comprises descriptive images associated with oriented points on the surface of an object. Constructed using single point bases, these images are data level shape descriptions that are used for efficient matching of oriented points. Correlation of images is used to establish point correspondences between two views; from these correspondences a rigid transformation that aligns the views is calculated. The transformation is then refined and verified using a modified iterative closest point algorithm. To demonstrate the generality of our approach, we present results from multiple sensing domains
Keywords :
image matching; image registration; image representation; iterative methods; object recognition; 3D free-form surface registration; data level shape descriptions; descriptive images; image correlation; image representation; iterative closest point algorithm; multiple sensing; object surface; oriented point matching; single point bases; view transformation; Contracts; Histograms; Indexing; Iterative closest point algorithm; Layout; Robot kinematics; Robot sensing systems; Shape; US Department of Energy; Voting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
3-D Digital Imaging and Modeling, 1997. Proceedings., International Conference on Recent Advances in
Conference_Location :
Ottawa, Ont.
Print_ISBN :
0-8186-7943-3
Type :
conf
DOI :
10.1109/IM.1997.603857
Filename :
603857
Link To Document :
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