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 proceedingConference contributionAcademicpeer-review

10 Citations (Scopus)
53 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 languageUndefined
Title of host publicationProceedings of the 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Place of PublicationSanta Barbara, California, USA
PublisherIEEE
Pages396-402
ISBN (Print)0-8186-8497-6
DOIs
Publication statusPublished - 23 Jun 1998

Publication series

Name
PublisherIEEE

Keywords

  • IR-16326
  • METIS-113211

Cite this

van Dop, E. R., & Regtien, P. P. L. (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 (pp. 396-402). Santa Barbara, California, USA: IEEE. https://doi.org/10.1109/CVPR.1998.698636
van Dop, E.R. ; Regtien, Paulus P.L. / Fitting undeformed superquadrics to range data: improving model recovery and classification. Proceedings of the 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Santa Barbara, California, USA : IEEE, 1998. pp. 396-402
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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. 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 proceedingConference contributionAcademicpeer-review

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AB - 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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van Dop ER, Regtien PPL. 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. Santa Barbara, California, USA: IEEE. 1998. p. 396-402 https://doi.org/10.1109/CVPR.1998.698636