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

Y. Sato, J. Ohya, K. Ishii

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publicationProceedings CVPR 1992 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition
PublisherIEEE Computer Society
Pages56-62
Number of pages7
ISBN (Electronic)0818628553
DOIs
Publication statusPublished - 1992 Jan 1
Externally publishedYes
Event1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 1992 - Champaign, United States
Duration: 1992 Jun 151992 Jun 18

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume1992-June
ISSN (Print)1063-6919

Conference

Conference1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 1992
CountryUnited States
CityChampaign
Period92/6/1592/6/18

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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  • 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