A statistical method for SVBRDF approximation from video sequences in general lighting conditions (Articolo in rivista)

Type
Label
  • A statistical method for SVBRDF approximation from video sequences in general lighting conditions (Articolo in rivista) (literal)
Anno
  • 2012-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1111/j.1467-8659.2012.03145.x (literal)
Alternative label
  • Palma G., Callieri M., Dellepiane M., Scopigno R. (2012)
    A statistical method for SVBRDF approximation from video sequences in general lighting conditions
    in Computer graphics forum (Online)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Palma G., Callieri M., Dellepiane M., Scopigno R. (literal)
Pagina inizio
  • 1491 (literal)
Pagina fine
  • 1500 (literal)
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  • Grant agreement 231809 Tipo Progetto EU_FP7 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://onlinelibrary.wiley.com/doi/10.1111/j.1467-8659.2012.03145.x/abstract (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 31 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 4 (literal)
Note
  • Scopu (literal)
  • PuMa (literal)
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; (literal)
Titolo
  • A statistical method for SVBRDF approximation from video sequences in general lighting conditions (literal)
Abstract
  • We present a statistical method for the estimation of the Spatially Varying Bidirectional Reflectance Distribution Function (SVBRDF) of an object with complex geometry, starting from video sequences acquired with fixed but general lighting conditions. The aim of this work is to define a method that simplifies the acquisition phase of the object surface appearance and allows to reconstruct an approximated SVBRDF. The final output is suitable to be used with a 3D model of the object to obtain accurate and photo-realistic renderings. The method is composed by three steps: the approximation of the environment map of the acquisition scene, using the same object as a probe; the estimation of the diffuse color of the object; the estimation of the specular components of the main materials of the object, by using a Phong model. All the steps are based on statistical analysis of the color samples projected by the video sequences on the surface of the object. Although the method presents some limitations, the trade-off between the easiness of acquisition and the obtained results makes it useful for practical applications. (literal)
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