Multiple comparison procedures
Multiple comparison procedures
Reflectance and texture of real-world surfaces
ACM Transactions on Graphics (TOG)
Illumination for computer generated pictures
Communications of the ACM
A signal-processing framework for inverse rendering
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Steerable illumination textures
ACM Transactions on Graphics (TOG)
Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons
International Journal of Computer Vision
Efficient rendering of spatial bi-directional reflectance distribution functions
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Bidirectional Reflection Distribution Function of Thoroughly Pitted Surfaces
International Journal of Computer Vision
A Wavelet Representation of Reflectance Functions
IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Specularities Reduce Ambiguity of Uncalibrated Photometric Stereo
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Appying Shape from Lighting Variation to Bump Map Capture
Proceedings of the Eurographics Workshop on Rendering Techniques '97
MVIEW '99 Proceedings of the IEEE Workshop on Multi-View Modeling & Analysis of Visual Scenes
Modeling Geometric Structure and Illumination Variation of a Scene from Real Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Capture and Synthesis of 3D Surface Texture
International Journal of Computer Vision - Special Issue on Texture Analysis and Synthesis
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Representing the appearances of surfaces illuminated from different directions has long been an active research topic. While many representation methods have been proposed, the relationships and conversion between different representations have been less well researched. These relationships are important, as they provide (a) an insight as to the different capabilities of the surface representations, and (b) a means by which they may be converted to common formats for computer graphic applications. In this paper, we introduce a single mathematical framework and use it to express three commonly used surface texture relighting representations: surface gradients (Gradient), Polynomial Texture Maps (PTM) and eigen base images (Eigen). The framework explicitly reveals the relations between the three methods, and from this we propose a set of conversion methods. We use 26 rough surface textures illuminated from 36 directions for our experiments and perform both quantitative and qualitative assessments to evaluate the conversion methods. The quantitative assessment uses a normalized root-mean-squared error as metric to compare the original images and those produced by proposed representation methods. The qualitative assessment is based on psychophysical experiments and non-parametric statistics. The results from the two assessments are consistent and show that the original Eigen representation produces the best performance. The second best performances are achieved by the original PTM representation and the conversion between Polynomial Texture Maps (PTM) and eigen base images (Eigen), while the performances of other representations are not significantly different.