Reflectance and texture of real-world surfaces
ACM Transactions on Graphics (TOG)
Toward a psychophysically-based light reflection model for image synthesis
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Reconstruction and representation of 3D objects with radial basis functions
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
A data-driven reflectance model
ACM SIGGRAPH 2003 Papers
APGV '05 Proceedings of the 2nd symposium on Applied perception in graphics and visualization
Verification of rendering quality from measured BTFs
APGV '06 Proceedings of the 3rd symposium on Applied perception in graphics and visualization
Interactive editing and modeling of bidirectional texture functions
ACM SIGGRAPH 2007 papers
AppWand: editing measured materials using appearance-driven optimization
ACM SIGGRAPH 2007 papers
Visual equivalence: towards a new standard for image fidelity
ACM SIGGRAPH 2007 papers
Interactive system for dynamic scene lighting using captured video environment maps
EGSR'05 Proceedings of the Sixteenth Eurographics conference on Rendering Techniques
A psychophysically validated metric for bidirectional texture data reduction
ACM SIGGRAPH Asia 2008 papers
Advanced textural representation of materials appearance
SIGGRAPH Asia 2011 Courses
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The use of illumination and view dependent textural information is one way to capture the realistic appearance of genuine materials. One example of such data is the bidirectional texture function. The main disadvantage of these data, that makes their further application very difficult, is their massive size. Perceptually-based methods can determine optimal uniform resampling of these data that allows considerable reduction of a number of view and illumination dependent samples. In this paper we propose to achieve this goal by means of a psychophysical study, comparing original data rendering with rendering of their uniformly resampled version over the hemisphere of illumination and view dependent textural measurements. The resampling was done separately for elevation and azimuthal angles as well as in illumination and view space. Our results shown promising consequences for compression and modeling algorithms using this kind of massive data.