The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
이 논문은 먼저 3D 객체에서 선형 거짓말 대수 모델의 불변량을 추출하는 강력한 알고리즘을 제시합니다. 특히, 법선 벡터의 정확한 추정치를 추출하기 위해 확장된 3D Hough 변환이 제시됩니다. 최소 제곱 피팅은 법선 벡터와 표현 행렬을 찾는 데 사용됩니다. 그런 다음 선형 거짓말 대수의 불변성을 사용하여 3D 객체에 대한 분할 알고리즘이 표시됩니다. 불변 공간과 물체 표면 모두에서의 불변 분포는 클러스터링 및 가장자리 감지에 사용됩니다.
3D 물체 인식, 허프 변환, 분할, 변하지 않는, 거짓말 대수학 모델
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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
부
@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},}
부
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 -