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First International Conference on Recent Advances in 3-D Digital Imaging and Modeling (3DIM '97)
Surface Registration by Matching Oriented Points
Ottawa, Ontario, Canada
May 12-May 15
ISBN: 0-8186-7943-3
ASCII Text
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A.E. Johnson, M. Hebert, "Surface Registration by Matching Oriented Points," 3D Digital Imaging and Modeling, International Conference on, pp. 121, First International Conference on Recent Advances in 3-D Digital Imaging and Modeling (3DIM '97), 1997.
 
 
BibTex
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@article{ 10.1109/IM.1997.603857,
author = {A.E. Johnson and M. Hebert},
title = {Surface Registration by Matching Oriented Points},
journal ={3D Digital Imaging and Modeling, International Conference on},
volume = {0},
year = {1997},
isbn = {0-8186-7943-3},
pages = {121},
doi = {http://doi.ieeecomputersociety.org/10.1109/IM.1997.603857},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - 3D Digital Imaging and Modeling, International Conference on
TI - Surface Registration by Matching Oriented Points
SN - 0-8186-7943-3
SP
EP
A1 - A.E. Johnson,
A1 - M. Hebert,
PY - 1997
KW - image registration; 3D free-form surface registration; oriented point matching; image representation; view transformation; descriptive images; object surface; single point bases; data level shape descriptions; image correlation; iterative closest point algorithm; multiple sensing
VL - 0
JA - 3D Digital Imaging and Modeling, International Conference on
ER -
 
A.E. Johnson, Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
M. Hebert, Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
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.
Index Terms:
image registration; 3D free-form surface registration; oriented point matching; image representation; view transformation; descriptive images; object surface; single point bases; data level shape descriptions; image correlation; iterative closest point algorithm; multiple sensing
Citation:
A.E. Johnson, M. Hebert, "Surface Registration by Matching Oriented Points," 3dim, pp.121, First International Conference on Recent Advances in 3-D Digital Imaging and Modeling (3DIM '97), 1997
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