Geometric and photometric data fusion in non-rigid shape analysis

Artiom Kovnatsky, Dan Raviv, Michael M. Bronstein*, Alexander M. Bronstein, Ron Kimmel

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

In this paper, we explore the use of the diffusion geometry framework for the fusion of geometric and photometric information in local and global shape descriptors. Our construction is based on the definition of a diffusion process on the shape manifold embedded into a high-dimensional space where the embedding coordinates represent the photometric information. Experimental results show that such data fusion is useful in coping with different challenges of shape analysis where pure geometric and pure photometric methods fail.

Original languageEnglish
Pages (from-to)199-222
Number of pages24
JournalNumerical Mathematics
Volume6
Issue number1
DOIs
StatePublished - Feb 2013
Externally publishedYes

Funding

FundersFunder number
European Commission
Seventh Framework Programme267414

    Keywords

    • 3D shape retrieval
    • Deformation invariance
    • Diffusion equation
    • Heat kernel descriptors
    • Laplace-Beltrami operator

    Fingerprint

    Dive into the research topics of 'Geometric and photometric data fusion in non-rigid shape analysis'. Together they form a unique fingerprint.

    Cite this