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

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Zeitschriftenartikel

Low-Level Images Cues in the Perception of Translucent Materials

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons83913

Fleming,  R
Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons83839

Bülthoff,  HH
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, 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

Fleming, R., & Bülthoff, H. (2005). Low-Level Images Cues in the Perception of Translucent Materials. ACM Transactions on Applied Perception, 2(3), 346-382. doi:doi.acm.org/10.1145/1077399.1077409.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-D50D-F
Zusammenfassung
When light strikes a translucent material (such as wax, milk or fruit flesh), it enters the body of the object, scatters and re-emerges from the surface. The diffusion of light through translucent materials gives them a characteristic visual softness and glow. What image properties underlie this distinctive appearance? What cues allow us to tell whether a surface is translucent or opaque? Previous work on the perception of semi-transparent materials was based on a very restricted physical model of thin filters [Metelli 1970; 1974a,b]. However, recent advances in computer graphics [Jensen et al. 2000; Jensen and Buhler 2002] allow us to efficiently simulate the complex sub-surface light transport effects that occur in real translucent objects. Here we use this model to study the perception of translucency, using a combination of psychophysics and image statistics. We find that many of the cues that were traditionally thought to be important for semi-transparent filters (e.g., X-junctions) are not relevant for solid translucent objects. We discuss the role of highlights, colour, object size, contrast, blur and lighting direction in the perception of translucency. We argue that the physics of translucency are too complex for the visual system to estimate intrinsic physical parameters by inverse optics. Instead, we suggest that we identify translucent materials by parsing them into key regions and by gathering image statistics from these regions.