IEICE TRANSACTIONS on Information
Invariant Extraction and Segmentation of 3D Objects Using Linear Lie Algebra Models
Summary :
This paper first presents robust algorithms to extract invariants of the linear Lie algebra model from 3D objects. In particular, an extended 3D Hough transform is presented to extract accurate estimates of the normal vectors. The Least square fitting is used to find normal vectors and representation matrices. Then an algorithm of segmentation for 3D objects is shown using the invariants of the linear Lie algebra. Distributions of invariants, both in the invariant space and on the object surface, are used for clustering and edge detection.
- Publication
- IEICE TRANSACTIONS on Information Vol.E85-D No.8 pp.1306-1313
- Publication Date
- 2002/08/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Image Processing, Image Pattern Recognition
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Masaki SUZUKI, Jinhui CHAO, "Invariant Extraction and Segmentation of 3D Objects Using Linear Lie Algebra Models" in IEICE TRANSACTIONS on Information,
vol. E85-D, no. 8, pp. 1306-1313, August 2002, doi: .
Abstract: This paper first presents robust algorithms to extract invariants of the linear Lie algebra model from 3D objects. In particular, an extended 3D Hough transform is presented to extract accurate estimates of the normal vectors. The Least square fitting is used to find normal vectors and representation matrices. Then an algorithm of segmentation for 3D objects is shown using the invariants of the linear Lie algebra. Distributions of invariants, both in the invariant space and on the object surface, are used for clustering and edge detection.
URL: https://global.ieice.org/en_transactions/information/10.1587/e85-d_8_1306/_p
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@ARTICLE{e85-d_8_1306,
author={Masaki SUZUKI, Jinhui CHAO, },
journal={IEICE TRANSACTIONS on Information},
title={Invariant Extraction and Segmentation of 3D Objects Using Linear Lie Algebra Models},
year={2002},
volume={E85-D},
number={8},
pages={1306-1313},
abstract={This paper first presents robust algorithms to extract invariants of the linear Lie algebra model from 3D objects. In particular, an extended 3D Hough transform is presented to extract accurate estimates of the normal vectors. The Least square fitting is used to find normal vectors and representation matrices. Then an algorithm of segmentation for 3D objects is shown using the invariants of the linear Lie algebra. Distributions of invariants, both in the invariant space and on the object surface, are used for clustering and edge detection.},
keywords={},
doi={},
ISSN={},
month={August},}
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TY - JOUR
TI - Invariant Extraction and Segmentation of 3D Objects Using Linear Lie Algebra Models
T2 - IEICE TRANSACTIONS on Information
SP - 1306
EP - 1313
AU - Masaki SUZUKI
AU - Jinhui CHAO
PY - 2002
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E85-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2002
AB - This paper first presents robust algorithms to extract invariants of the linear Lie algebra model from 3D objects. In particular, an extended 3D Hough transform is presented to extract accurate estimates of the normal vectors. The Least square fitting is used to find normal vectors and representation matrices. Then an algorithm of segmentation for 3D objects is shown using the invariants of the linear Lie algebra. Distributions of invariants, both in the invariant space and on the object surface, are used for clustering and edge detection.
ER -
English
