Smoothed local generalized cones: An axial representation of 3D shapes

Y. Sato; J. Ohya; K. Ishii

doi:10.1109/CVPR.1992.223227

Smoothed local generalized cones: An axial representation of 3D shapes

Y. Sato, J. Ohya, K. Ishii

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

The recovery of viewpoint-independent descriptions of 3D shapes from two-and-one-half dimensional images. A novel 3D shape representation called the smoothed local generalized cones (SLGCs) is proposed. This representation is suitable for recovery of the axis, because the local constraint that characterizes a data set corresponding to the same axis point, namely, the local generalized cone (LGC), is explicitly defined. The extracted axis can be used as a basis for determining a natural parameterization of the object surface. Using this parameterization, the deformable surface fitting problem results in a linear least-squares problem, so stable volumetric recovery is possible. Recovery experiments involving real 3D range images are reported.

Original language	English
Title of host publication	Proceedings CVPR 1992 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Publisher	IEEE Computer Society
Pages	56-62
Number of pages	7
ISBN (Electronic)	0818628553
DOIs	https://doi.org/10.1109/CVPR.1992.223227
Publication status	Published - 1992 Jan 1
Externally published	Yes
Event	1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 1992 - Champaign, United States Duration: 1992 Jun 15 → 1992 Jun 18

Publication series

Name	Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume	1992-June
ISSN (Print)	1063-6919

Conference

Conference	1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 1992
Country	United States
City	Champaign
Period	92/6/15 → 92/6/18

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition

Access to Document

10.1109/CVPR.1992.223227

Fingerprint Dive into the research topics of 'Smoothed local generalized cones: An axial representation of 3D shapes'. Together they form a unique fingerprint.

Cite this

Sato, Y., Ohya, J., & Ishii, K. (1992). Smoothed local generalized cones: An axial representation of 3D shapes. In Proceedings CVPR 1992 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 56-62). [223227] (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; Vol. 1992-June). IEEE Computer Society. https://doi.org/10.1109/CVPR.1992.223227

Smoothed local generalized cones : An axial representation of 3D shapes. / Sato, Y.; Ohya, J.; Ishii, K.

Proceedings CVPR 1992 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society, 1992. p. 56-62 223227 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; Vol. 1992-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Sato, Y, Ohya, J & Ishii, K 1992, Smoothed local generalized cones: An axial representation of 3D shapes. in Proceedings CVPR 1992 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition., 223227, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1992-June, IEEE Computer Society, pp. 56-62, 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 1992, Champaign, United States, 92/6/15. https://doi.org/10.1109/CVPR.1992.223227

Sato Y, Ohya J, Ishii K. Smoothed local generalized cones: An axial representation of 3D shapes. In Proceedings CVPR 1992 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society. 1992. p. 56-62. 223227. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition). https://doi.org/10.1109/CVPR.1992.223227

@inproceedings{dc53a35454f24edeb643548bf70b3797,

title = "Smoothed local generalized cones: An axial representation of 3D shapes",

abstract = "The recovery of viewpoint-independent descriptions of 3D shapes from two-and-one-half dimensional images. A novel 3D shape representation called the smoothed local generalized cones (SLGCs) is proposed. This representation is suitable for recovery of the axis, because the local constraint that characterizes a data set corresponding to the same axis point, namely, the local generalized cone (LGC), is explicitly defined. The extracted axis can be used as a basis for determining a natural parameterization of the object surface. Using this parameterization, the deformable surface fitting problem results in a linear least-squares problem, so stable volumetric recovery is possible. Recovery experiments involving real 3D range images are reported.",

author = "Y. Sato and J. Ohya and K. Ishii",

year = "1992",

month = jan,

day = "1",

doi = "10.1109/CVPR.1992.223227",

language = "English",

series = "Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition",

publisher = "IEEE Computer Society",

pages = "56--62",

booktitle = "Proceedings CVPR 1992 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition",

note = "1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 1992 ; Conference date: 15-06-1992 Through 18-06-1992",

}

TY - GEN

T1 - Smoothed local generalized cones

T2 - 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 1992

AU - Sato, Y.

AU - Ohya, J.

AU - Ishii, K.

PY - 1992/1/1

Y1 - 1992/1/1

N2 - The recovery of viewpoint-independent descriptions of 3D shapes from two-and-one-half dimensional images. A novel 3D shape representation called the smoothed local generalized cones (SLGCs) is proposed. This representation is suitable for recovery of the axis, because the local constraint that characterizes a data set corresponding to the same axis point, namely, the local generalized cone (LGC), is explicitly defined. The extracted axis can be used as a basis for determining a natural parameterization of the object surface. Using this parameterization, the deformable surface fitting problem results in a linear least-squares problem, so stable volumetric recovery is possible. Recovery experiments involving real 3D range images are reported.

AB - The recovery of viewpoint-independent descriptions of 3D shapes from two-and-one-half dimensional images. A novel 3D shape representation called the smoothed local generalized cones (SLGCs) is proposed. This representation is suitable for recovery of the axis, because the local constraint that characterizes a data set corresponding to the same axis point, namely, the local generalized cone (LGC), is explicitly defined. The extracted axis can be used as a basis for determining a natural parameterization of the object surface. Using this parameterization, the deformable surface fitting problem results in a linear least-squares problem, so stable volumetric recovery is possible. Recovery experiments involving real 3D range images are reported.

UR - http://www.scopus.com/inward/record.url?scp=33747487793&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33747487793&partnerID=8YFLogxK

U2 - 10.1109/CVPR.1992.223227

DO - 10.1109/CVPR.1992.223227

M3 - Conference contribution

AN - SCOPUS:33747487793

T3 - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

SP - 56

EP - 62

BT - Proceedings CVPR 1992 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition

PB - IEEE Computer Society

Y2 - 15 June 1992 through 18 June 1992

ER -