Texture discrimination by Gabor functions
Biological Cybernetics
Multichannel Texture Analysis Using Localized Spatial Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational models of visual processing
Computational models of visual processing
Unsupervised texture segmentation using Gabor filters
Pattern Recognition
Periodicity, Directionality, and Randomness: Wold Features for Image Modeling and Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast texture synthesis using tree-structured vector quantization
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
I3D '01 Proceedings of the 2001 symposium on Interactive 3D graphics
Texture features for content-based retrieval
Principles of visual information retrieval
Fuzzy-System in Computer Science
Fuzzy-System in Computer Science
Human and Machine Vision: Symposium
Human and Machine Vision: Symposium
Significantly Different Textures: A Computational Model of Pre-attentive Texture Segmentation
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
International Journal of Computer Vision - Special Issue on Texture Analysis and Synthesis
Low-Level Image Cues in the Perception of Translucent Materials
ACM Transactions on Applied Perception (TAP)
Perceptual texture space improves perceptual consistency of computational features
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Emotion-based textile indexing using colors, texture and patterns
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part II
Natural / man-made object classification based on gabor characteristics
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
Studying aesthetics in photographic images using a computational approach
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
FLEXFIS: A Robust Incremental Learning Approach for Evolving Takagi–Sugeno Fuzzy Models
IEEE Transactions on Fuzzy Systems
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Texture is extensively used in areas such as product design and architecture to convey specific aesthetic information. Using the results of a psychological experiment, we model the relationship between computational texture features and aesthetic properties of visual textures. Contrary to previous approaches, we build a layered model, which provides insights into hierarchical relationships involved in human aesthetic texture perception. This model uses a set of intermediate judgements to link computational texture features with aesthetic texture properties. We pursue two different approaches for modeling. (1) Supervised machine-learning methods are used to generate linear and nonlinear models from the experimental data automatically. The quality of these models is discussed, mainly focusing on interpretability and accuracy. (2) We apply a psychological-based approach that models the processing pathways in human perception of naturalness, introducing judgement dimensions (principal components) mediating the relationship between texture features and naturalness judgements. This multiple mediator model serves as a verification of the machine-learning approach. We conclude with a comparison of these two approaches, highlighting the similarities and discrepancies in terms of identified relationships between computational texture features and aesthetic properties of visual textures.