Efficient registration of 3D SPHARM surfaces

Li Shen, Heng Huang, Fillia Makedon, Andrew J. Saykin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Scopus citations

Abstract

We present SHREC, an efficient algorithm for registration of 3D SPHARM (spherical harmonic) surfaces. SHREC follows the iterative closest point (ICP) registration strategy, and alternately improves the surface correspondence and adjusts the object pose. It establishes the surface correspondence by aligning the underlying SPHARM parameterization. It employs a rotational property of the harmonic expansion to accelerate its step for parameterization rotation. It uses a hierarchical icosahedron approach to sample the rotation space and searches for the best parameterization that matches the template. Our experimental results show that SHREC can not only create more accurate registration than previous methods but also do it efficiently. SHREC is a simple, efficient and general registration method, and has a great potential to be used in many shape modeling and analysis applications.

Original languageEnglish (US)
Title of host publicationProceedings - Fourth Canadian Conference on Computer and Robot Vision, CRV 2007
Pages81-88
Number of pages8
DOIs
StatePublished - Sep 25 2007
Event4th Canadian Conference on Computer and Robot Vision, CRV 2007 - Montreal, QC, Canada
Duration: May 28 2007May 30 2007

Publication series

NameProceedings - Fourth Canadian Conference on Computer and Robot Vision, CRV 2007

Other

Other4th Canadian Conference on Computer and Robot Vision, CRV 2007
CountryCanada
CityMontreal, QC
Period5/28/075/30/07

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Software

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  • Cite this

    Shen, L., Huang, H., Makedon, F., & Saykin, A. J. (2007). Efficient registration of 3D SPHARM surfaces. In Proceedings - Fourth Canadian Conference on Computer and Robot Vision, CRV 2007 (pp. 81-88). [4228526] (Proceedings - Fourth Canadian Conference on Computer and Robot Vision, CRV 2007). https://doi.org/10.1109/CRV.2007.26