de.mpg.escidoc.pubman.appbase.FacesBean
Deutsch
 
Hilfe Wegweiser Impressum Kontakt Einloggen
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Konferenzbeitrag

Adaptive Acquisition of Lumigraphs from Synthetic Scenes

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons45390

Schirmacher,  Hartmut
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44602

Heidrich,  Wolfgang
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45449

Seidel,  Hans-Peter
Computer Graphics, MPI for Informatics, Max Planck Society;

Externe Ressourcen
Es sind keine Externen Ressourcen verfügbar
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Schirmacher, H., Heidrich, W., & Seidel, H.-P. (1999). Adaptive Acquisition of Lumigraphs from Synthetic Scenes. In P. Brunet, & R. Scopigno (Eds.), Proceedings of the 20th Annual Conference ot the European Association of Computer Graphics (Eurographics-99) (pp. 151-160). Oxford, USA: Blackwell.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-36AC-4
Zusammenfassung
Light fields and Lumigraphs are capable of rendering scenes of arbitrary geometrical or illumination complexity in real time. They are thus interesting ways of interacting with both recorded real-world and high-quality synthetic scenes. Unfortunately, both light fields and Lumigraph rely on a dense sampling of the illumination to provide a good rendering quality. This induces high costs both in terms of storage requirements and computational resources for the image acquisition. Techniques for acquiring adaptive light field and Lumigraph representations are thus mandatory for practical applications. In this paper we present a method for the adaptive acquisition of images for Lumigraphs from synthetic scenes. Using image warping to predict the potential improvement in image quality when adding a certain view, we decide which new views of the scene should be rendered and added to the light field. This a-priori error estimator accounts for both visibility problems and illumination effects such as specular highlights.