title: Aesthetics by Numbers: Links between Perceived Texture Qualities and Computed Visual Texture Properties.
abstract: Our world is filled with texture. For the human visual system, this is an important source of information for assessing environmental and material properties. Indeed-and presumably for this reason-the human visual system has regions dedicated to processing textures. Despite their abundance and apparent relevance, only recently the relationships between texture features and high-level judgments have captured the interest of mainstream science, despite long-standing indications for such relationships. In this study, we explore such relationships, as these might be used to predict perceived texture qualities. This is relevant, not only from a psychological/neuroscience perspective, but also for more applied fields such as design, architecture, and the visual arts. In two separate experiments, observers judged various qualities of visual textures such as beauty, roughness, naturalness, elegance, and complexity. Based on factor analysis, we find that in both experiments, ~75% of the variability in the judgments could be explained by a two-dimensional space, with axes that are closely aligned to the beauty and roughness judgments. That a two-dimensional judgment space suffices to capture most of the variability in the perceived texture qualities suggests that observers use a relatively limited set of internal scales on which to base various judgments, including aesthetic ones. Finally, for both of these judgments, we determined the relationship with a large number of texture features computed for each of the texture stimuli. We find that the presence of lower spatial frequencies, oblique orientations, higher intensity variation, higher saturation, and redness correlates with higher beauty ratings. Features that captured image intensity and uniformity correlated with roughness ratings. Therefore, a number of computational texture features are predictive of these judgments. This suggests that perceived texture qualities-including the aesthetic appreciation-are sufficiently universal to be predicted-with reasonable accuracy-based on the computed feature content of the textures.
authors: Laboratory for Experimental Ophthalmology, University Medical Center Groningen, University of GroningenGroningen, Netherlands; Donders Institute for Brain, Cognition and Behavior, Donders Center for Cognition, Radboud UniversityNijmegen, Netherlands.
authors: Richard H A H
authors: RH
authors: Jacobs
authors: Laboratory for Experimental Ophthalmology, University Medical Center Groningen, University of GroningenGroningen, Netherlands; Donders Institute for Brain, Cognition and Behavior, Centre for Cognitive Neuroimaging, Radboud UniversityNijmegen, Netherlands.
authors: Koen V
authors: KV
authors: Haak
authors: Profactor GmbHSteyr-Gleink, Austria; Research Unit for Medical-Informatics, RISC Software GmbH, Johannes Kepler University LinzLinz, Austria.
authors: Stefan
authors: S
authors: Thumfart
authors: Laboratory for Experimental Ophthalmology, University Medical Center Groningen, University of GroningenGroningen, Netherlands; BCN NeuroImaging Center, School for Behavioral and Cognitive Neurosciences, University Medical Center GroningenUniversity of Groningen, Groningen, Netherlands.
authors: Remco
authors: R
authors: Renken
authors: School of Mechanical Engineering, University of Leeds Leeds, UK.
authors: Brian
authors: B
authors: Henson
authors: Laboratory for Experimental Ophthalmology, University Medical Center Groningen, University of Groningen Groningen, Netherlands.
authors: Frans W
authors: FW
authors: Cornelissen
keywords: aesthetics; beauty; descriptive; evaluative; features; roughness; semantic differential; texture perception