Heat Diffusion Kernel and Distance on Surface Meshes and Point Sets (Articolo in rivista)

Type
Label
  • Heat Diffusion Kernel and Distance on Surface Meshes and Point Sets (Articolo in rivista) (literal)
Anno
  • 2013-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1016/j.cag.2013.05.019 (literal)
Alternative label
  • Giuseppe Patané , MichelaSpagnuolo (2013)
    Heat Diffusion Kernel and Distance on Surface Meshes and Point Sets
    in Computers & graphics; Elsevier Ltd, Oxford (Regno Unito)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Giuseppe Patané , MichelaSpagnuolo (literal)
Pagina inizio
  • 676 (literal)
Pagina fine
  • 686 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni
  • Shape Modeling International (SMI) Conference 2013 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.sciencedirect.com/science/article/pii/S0097849313000939 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 37 (literal)
Rivista
Note
  • ISI Web of Science (WOS) (literal)
  • Scopu (literal)
  • Google Scholar (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Consiglio Nazionale delle Ricerche, Istituto di Matematica Applicata e Tecnologie Informatiche, Via D eMarini, 6, 16149 Genova, Italy (literal)
Titolo
  • Heat Diffusion Kernel and Distance on Surface Meshes and Point Sets (literal)
Abstract
  • The heat diffusion distance and kernel have gained a central role in geometry processing and shape analysis. This paper addresses a novel discretization and spectrum-free computation of the diffusion kernel and distance on a 3D shape PP represented as a triangle mesh or a point set. After rewriting different discretizations of the Laplace-Beltrami operator in a unified way and using an intrinsic scalar product on the space of functions on PP, we derive a shape-intrinsic heat kernel matrix, together with the corresponding diffusion distances. Then, we propose an efficient computation of the heat distance and kernel through the solution of a set of sparse linear systems. In this way, we bypass the evaluation of the Laplacian spectrum, the selection of a specific subset of eigenpairs, and the use of multi-resolutive prolongation operators. The comparison with previous work highlights the main features of the proposed approach in terms of smoothness, stability to shape discretization, approximation accuracy, and computational cost (literal)
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