Texture space
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Updated: Oct 9, 2026

Photorealistic Learned Landscapes for Augmented Reality
Published on: June 27, 2025
1Department of Psychology, Concordia University, 7141 Sherbrooke Street West, Québec, H4B 1R6, Montréal, Canada. gurnsey@vax2.concordia.ca
Abstract:
Many previous studies have examined the ease with which two spatially adjacent textures can be segmented. Our goal is to examine the representational system that determines the appearance of isolated patches of visual texture. To this end, similarity judgments from three subjects were obtained for 20 artificial textures comprising filtered noise. Multidimensional scaling (MDS) revealed that three perceptual dimensions explain most of the variance in subjects' similarity judgments. In addition, the three subjects' similarity judgments and MDS solutions were highly correlated. A computational model utilizing the energy responses in seven bandpass filters explains an average of 80% of the variability in the original similarity scores of individual subjects. In the model, energy responses are mapped to the perceptual space through a linear transformation that can be decomposed into two components. The first component decorrelates initial filter responses and the second component maps the decorrelated filter responses to a perceptual space. These latter transformations show remarkable agreement between the three subjects.
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