Fitting undeformed superquadrics to range data: improving model recovery and classification

E.R. van Dop; Paulus P.L. Regtien

doi:10.1109/CVPR.1998.698636

Fitting undeformed superquadrics to range data: improving model recovery and classification

E.R. van Dop
, Paulus P.L. Regtien

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

17 Citations (Scopus)

938 Downloads (Pure)

Abstract

Undeformed superquadrics are volumetric modeling primitives with an extensive shape vocabulary that are described by only 5 parameters. Fitting these models viewpoint invariantly to range data enables classification based on the superquadric parameters. However, current recovery routines show several limitations, especially when the algorithms are applied to range images instead of true 3D images. In this paper problems with the common superquadric recovery procedure are identified and solutions are presented

Original language	Undefined
Title of host publication	Proceedings of the 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Place of Publication	Santa Barbara, California, USA
Publisher	IEEE
Pages	396-402
ISBN (Print)	0-8186-8497-6
DOIs	https://doi.org/10.1109/CVPR.1998.698636
Publication status	Published - 23 Jun 1998
Event	IEEE Conference on Computer Vision and Pattern Recognition, CVPR 1998 - Santa Barbara, United States Duration: 23 Jun 1998 → 25 Jun 1998

Publication series

Name
Publisher	IEEE

Conference

Conference	IEEE Conference on Computer Vision and Pattern Recognition, CVPR 1998
Abbreviated title	CVPR 1998
Country/Territory	United States
City	Santa Barbara
Period	23/06/98 → 25/06/98

Keywords

IR-16326
METIS-113211

Access to Document

10.1109/CVPR.1998.698636

00698636

Cite this

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title = "Fitting undeformed superquadrics to range data: improving model recovery and classification",

abstract = "Undeformed superquadrics are volumetric modeling primitives with an extensive shape vocabulary that are described by only 5 parameters. Fitting these models viewpoint invariantly to range data enables classification based on the superquadric parameters. However, current recovery routines show several limitations, especially when the algorithms are applied to range images instead of true 3D images. In this paper problems with the common superquadric recovery procedure are identified and solutions are presented",

keywords = "IR-16326, METIS-113211",

author = "\{van Dop\}, E.R. and Regtien, \{Paulus P.L.\}",

year = "1998",

month = jun,

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doi = "10.1109/CVPR.1998.698636",

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publisher = "IEEE",

pages = "396--402",

booktitle = "Proceedings of the 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition",

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note = "IEEE Conference on Computer Vision and Pattern Recognition, CVPR 1998 ; Conference date: 23-06-1998 Through 25-06-1998",

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van Dop, ER & Regtien, PPL 1998, Fitting undeformed superquadrics to range data: improving model recovery and classification. in Proceedings of the 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE, Santa Barbara, California, USA, pp. 396-402, IEEE Conference on Computer Vision and Pattern Recognition, CVPR 1998, Santa Barbara, California, United States, 23/06/98. https://doi.org/10.1109/CVPR.1998.698636

Fitting undeformed superquadrics to range data: improving model recovery and classification. / van Dop, E.R.; Regtien, Paulus P.L.
Proceedings of the 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Santa Barbara, California, USA: IEEE, 1998. p. 396-402.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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N2 - Undeformed superquadrics are volumetric modeling primitives with an extensive shape vocabulary that are described by only 5 parameters. Fitting these models viewpoint invariantly to range data enables classification based on the superquadric parameters. However, current recovery routines show several limitations, especially when the algorithms are applied to range images instead of true 3D images. In this paper problems with the common superquadric recovery procedure are identified and solutions are presented

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KW - IR-16326

KW - METIS-113211

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