Proceedings of the 25th annual conference on Computer graphics and interactive techniques
A practical model for subsurface light transport
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
A practical model for subsurface light transport
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
A rapid hierarchical rendering technique for translucent materials
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Low-Level Image Cues in the Perception of Translucent Materials
ACM Transactions on Applied Perception (TAP)
Psychophysical evaluation of animated facial expressions
APGV '05 Proceedings of the 2nd symposium on Applied perception in graphics and visualization
Interactive editing and modeling of bidirectional texture functions
ACM SIGGRAPH 2007 papers
Evaluating the perceptual realism of animated facial expressions
ACM Transactions on Applied Perception (TAP)
Digital Modeling of Material Appearance
Digital Modeling of Material Appearance
Toward a perceptual space for gloss
ACM Transactions on Graphics (TOG)
The State of the Art in Interactive Global Illumination
Computer Graphics Forum
Optimizing environment maps for material depiction
EGSR'11 Proceedings of the Twenty-second Eurographics conference on Rendering
Understanding the role of phase function in translucent appearance
ACM Transactions on Graphics (TOG)
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Many common materials, including fruit, wax and human skin, are somewhat translucent. What makes an object look translucent or opaque? Here we use a recently developed computer graphics model of subsurface light transport [Jensen, et al., 2001] to study the factors that determine perceived translucency. We discuss how physical factors, such as light-source direction can alter the apparent translucency of an object, finding that objects are perceived to be more translucent when illuminated from behind than in front. We also study the role of a range of image cues, including colour, contrast and blur, in the perception of translucency. Although we learn a lot about images of translucent materials, we find that many simple candidate sources of information fail to predict how translucent an object looks. We suggest that the visual system does not rely solely on these simple image statistics to estimate translucency: the relevant stimulus information remains to be discovered.