Discrete-time signal processing
Discrete-time signal processing
Surface Orientation from Projective Foreshortening of Isotropic Texture Autocorrelation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape from texture using the Wigner distribution
Computer Vision, Graphics, and Image Processing
Handbook of pattern recognition & computer vision
Shape from Texture Using Local Spectral Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generalization of the Lambertian model and implications for machine vision
International Journal of Computer Vision
Matrix computations (3rd ed.)
Reflectance and texture of real-world surfaces
ACM Transactions on Graphics (TOG)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bidirectional Reflection Distribution Function Expressed in Terms of Surface Scattering Modes
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
On Perpendicular Texture: Why do we see more flowers in the distance?
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Reflectance and Texture of Real-World Surfaces Authors
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Histogram Model for 3D Textures
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Texture segmentation and shape in the same image
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Eigen-Texture Method: Appearance Compression and Synthesis Based on a 3D Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Synthesis of bidirectional texture functions on arbitrary surfaces
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Texture modelling by discrete distribution mixtures
Computational Statistics & Data Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D Texture Recognition Using Bidirectional Feature Histograms
International Journal of Computer Vision
A Six-Stimulus Theory for Stochastic Texture
International Journal of Computer Vision - Special Issue on Texture Analysis and Synthesis
A Statistical Approach to Texture Classification from Single Images
International Journal of Computer Vision - Special Issue on Texture Analysis and Synthesis
International Journal of Computer Vision - Special Issue on Texture Analysis and Synthesis
Illumination invariant recognition of three-dimensional texture in color images
Journal of Computer Science and Technology
Image retrieval measures based on illumination invariant textural MRF features
Proceedings of the 6th ACM international conference on Image and video retrieval
Journal of Mathematical Imaging and Vision
A psychophysically validated metric for bidirectional texture data reduction
ACM SIGGRAPH Asia 2008 papers
Material-specific adaptation of color invariant features
Pattern Recognition Letters
Advanced textural representation of materials appearance
SIGGRAPH Asia 2011 Courses
Texture recognition using robust Markovian features
MUSCLE'11 Proceedings of the 2011 international conference on Computational Intelligence for Multimedia Understanding
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The observed image texture for a rough surface has a complex dependence on the illumination and viewing angles due to effects such as foreshortening, local shading, interreflections, and the shadowing and occlusion of surface elements. We introduce the dimensionality surface as a representation for the visual complexity of a material sample. The dimensionality surface defines the number of basis textures that are required to represent the observed textures for a sample as a function of ranges of illumination and viewing angles. Basis textures are represented using multiband correlation functions that consider both within and between color band correlations. We examine properties of the dimensionality surface for real materials using the Columbia Utrecht Reflectance and Texture (CUReT) database. The analysis shows that the dependence of the dimensionality surface on ranges of illumination and viewing angles is approximately linear with a slope that depends on the complexity of the sample. We extend the analysis to consider the problem of recognizing rough surfaces in color images obtained under unknown illumination and viewing geometry. We show, using a set of 12,505 images from 61 material samples, that the information captured by the multiband correlation model allows surfaces to be recognized over a wide range of conditions. We also show that the use of color information provides significant advantages for three-dimensional texture recognition.