Texture space.

R Gurnsey; D J Fleet

doi:10.1016/s0042-6989(00)00307-2

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PubMed · 11248263

Texture space.

R Gurnsey·D J Fleet

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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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Form Perception Humans Least-Squares Analysis Linear Models Male Observer Variation Space Perception Statistics, Nonparametric Journal Article Research Support, Non-U.S. Gov't

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R Gurnsey, D J Fleet. 2001. Texture space.. https://doi.org/10.1016/s0042-6989(00)00307-2

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