A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Prior Learning and Gibbs Reaction-Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing Surfaces Using Three-Dimensional Textons
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Transformed Component Analysis: Joint Estimation of Spatial Transformations and Image Components
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Modeling natural microimage statistics
Modeling natural microimage statistics
Data compression and harmonic analysis
IEEE Transactions on Information Theory
Image compression via joint statistical characterization in the wavelet domain
IEEE Transactions on Image Processing
Motion texture: a two-level statistical model for character motion synthesis
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
On Advances in Statistical Modeling of Natural Images
Journal of Mathematical Imaging and Vision
Modeling Visual Patterns by Integrating Descriptive and Generative Methods
International Journal of Computer Vision
EGRW '03 Proceedings of the 14th Eurographics workshop on Rendering
The Promise and Perils of Near-Regular Texture
International Journal of Computer Vision - Special Issue on Texture Analysis and Synthesis
International Journal of Computer Vision - Special Issue on Texture Analysis and Synthesis
An evolutionary system for near-regular texture synthesis
Pattern Recognition
International Journal of Computer Vision
Computation of generic features for object classification
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
Image features and the 1-D, 2nd
Scale-Space'05 Proceedings of the 5th international conference on Scale Space and PDE Methods in Computer Vision
Noisy iris image matching by using multiple cues
Pattern Recognition Letters
Distributional semantics in technicolor
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
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Textons refer to fundamental micro-structures in generic natural images and thus constitute the basic elements in early (preattentive) visual perception. However, the word "texton" remains a vague concept in the literature of computer vision and visual perception, and a precise mathematical definition has yet to be found. In this article, we argue that the definition of texton should be governed by a sound mathematical model of images, and the set of textons must be learned from, or best tuned to, an image ensemble. We adopt a generative image model that an image is a superposition of bases from an over-complete dictionary, then a texton is defined as a mini-template that consists of a varying number of image bases with some geometric and photometric configurations. By analogy to physics, if image bases are like protons, neutrons and electrons, then textons are like atoms. Then a small number of textons can be learned from training images as repeating micro-structures. We report four experiments for comparison. The first experiment computes clusters in feature space of filter responses. The second use transformed component analysis in both feature space and image patches. The third adopts a two-layer generative model where an image is generated by image bases and image bases are generated by textons. The fourth experiment shows textons from motion image sequences, which we call movetons.