Automatic Classification of Objects in 3D
Laser Range Scans
A. Nüchter, H. Surmann, and J. Hertzberg. Proceedings of the 8th Conference on Intelligent
Autonomous Systems (IAS '04), page 963--970. Amsterdam, The Netherlands, (March 2004)
Abstract
3D models of the skin surface of patients are
created by ultra-fast holography and automatic scan
matching of synchronously recorded holograms. By
recording with a pulsed laser and continuous-wave
optical reconstruction of the holographic real
image, motion artifacts are eliminated. Focal analys
is of the real image yields a surface relief of the
patient. To generate a complete 360 patient model,
several synchronously recorded reliefs are
registered by automatic scan matching. We find the
transformation consisting of a rotation and a
translation that minimizes a cost function
containing the Euclidian distances between points
pairs from two surface relief maps. A variant of the
ICP (Iterative Closest Points) algorithm2 is used to
compute such a minimum. We propose a new fast
approximation based on kDtrees for the problem of
creating the closest point pairs on which the ICP
algorithm spends most of its time.
%0 Conference Paper
%1 IAS2004
%A Nüchter, A.
%A Surmann, H.
%A Hertzberg, J.
%B Proceedings of the 8th Conference on Intelligent
Autonomous Systems (IAS '04)
%C Amsterdam, The Netherlands
%D 2004
%K imported
%P 963--970
%T Automatic Classification of Objects in 3D
Laser Range Scans
%U https://robotik.informatik.uni-wuerzburg.de/telematics/download/mrnv2004.pdf
%X 3D models of the skin surface of patients are
created by ultra-fast holography and automatic scan
matching of synchronously recorded holograms. By
recording with a pulsed laser and continuous-wave
optical reconstruction of the holographic real
image, motion artifacts are eliminated. Focal analys
is of the real image yields a surface relief of the
patient. To generate a complete 360 patient model,
several synchronously recorded reliefs are
registered by automatic scan matching. We find the
transformation consisting of a rotation and a
translation that minimizes a cost function
containing the Euclidian distances between points
pairs from two surface relief maps. A variant of the
ICP (Iterative Closest Points) algorithm2 is used to
compute such a minimum. We propose a new fast
approximation based on kDtrees for the problem of
creating the closest point pairs on which the ICP
algorithm spends most of its time.
@inproceedings{IAS2004,
abstract = {3D models of the skin surface of patients are
created by ultra-fast holography and automatic scan
matching of synchronously recorded holograms. By
recording with a pulsed laser and continuous-wave
optical reconstruction of the holographic real
image, motion artifacts are eliminated. Focal analys
is of the real image yields a surface relief of the
patient. To generate a complete 360 patient model,
several synchronously recorded reliefs are
registered by automatic scan matching. We find the
transformation consisting of a rotation and a
translation that minimizes a cost function
containing the Euclidian distances between points
pairs from two surface relief maps. A variant of the
ICP (Iterative Closest Points) algorithm2 is used to
compute such a minimum. We propose a new fast
approximation based on kDtrees for the problem of
creating the closest point pairs on which the ICP
algorithm spends most of its time. },
added-at = {2017-09-19T13:40:53.000+0200},
address = {Amsterdam, The Netherlands},
author = {N{\"u}chter, A. and Surmann, H. and Hertzberg, J.},
biburl = {https://www.bibsonomy.org/bibtex/2df5b7e16de0329aeadcf14ad05f0b96c/nuechter76},
booktitle = {Proceedings of the 8th Conference on Intelligent
Autonomous Systems (IAS '04)},
interhash = {fad2c866497cae9523d2342688a62b33},
intrahash = {df5b7e16de0329aeadcf14ad05f0b96c},
keywords = {imported},
month = {March},
pages = {963--970},
timestamp = {2017-09-29T16:01:21.000+0200},
title = {{A}utomatic {C}lassification of {O}bjects in {3D}
{L}aser {R}ange {S}cans},
url = {https://robotik.informatik.uni-wuerzburg.de/telematics/download/mrnv2004.pdf},
year = 2004
}