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16th International Conference on Pattern Recognition (ICPR'02) - Volume 3
The Trimmed Iterative Closest Point Algorithm
Quebec City, QC, Canada
August 11-August 15
ISBN: 0-7695-1695-X
ASCII Text
x 
 
D. Chetverikov, D. Svirko, D. Stepanov, Pavel Krsek, "The Trimmed Iterative Closest Point Algorithm," Pattern Recognition, International Conference on, vol. 3, pp. 30545, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 3, 2002.
 
 
BibTex
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@article{ 10.1109/ICPR.2002.1047997,
author = {D. Chetverikov and D. Svirko and D. Stepanov and Pavel Krsek},
title = {The Trimmed Iterative Closest Point Algorithm},
journal ={Pattern Recognition, International Conference on},
volume = {3},
year = {2002},
issn = {1051-4651},
pages = {30545},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.1047997},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Pattern Recognition, International Conference on
TI - The Trimmed Iterative Closest Point Algorithm
SN - 1051-4651
SP
EP
A1 - D. Chetverikov,
A1 - D. Svirko,
A1 - D. Stepanov,
A1 - Pavel Krsek,
PY - 2002
KW - null
VL - 3
JA - Pattern Recognition, International Conference on
ER -
 
D. Chetverikov, Computer and Automation Institute
D. Svirko, Computer and Automation Institute
D. Stepanov, Computer and Automation Institute
Pavel Krsek, Czech Technical University
The problem of geometric alignment of two roughly preregistered, partially overlapping, rigid, noisy 3D point sets is considered. A new natural and simple, robustified extension of the popular Iterative Closest Point (ICP) algorithm [1] is presented, called the Trimmed ICP (TrICP). The new algorithm is based on the consistent use of the Least Trimmed Squares (LTS) approach in all phases of the operation. Convergence is proved and an efficient implementation is discussed. TrICP is fast, applicable to overlaps under 50%, robust to erroneous measurements and shape defects, and has easy-to-set parameters. ICP is a special case of TrICP when the overlap parameter is 100%. Results of testing the new algorithm are shown.
Citation:
D. Chetverikov, D. Svirko, D. Stepanov, Pavel Krsek, "The Trimmed Iterative Closest Point Algorithm," icpr, vol. 3, pp.30545, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 3, 2002
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