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Martin Giesel, Qasim Zaidi; Adaptation reveals frequency band based inferences of material properties. Journal of Vision 2012;12(9):950. doi: 10.1167/12.9.950.
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© ARVO (1962-2015); The Authors (2016-present)
Rapid and reliable identification of material properties is important for successful interactions with the environment. Real materials exhibit characteristic configurations of low-level features and it is possible that features corresponding to particular properties are present generically and are stored as knowledge by human observers. We demonstrated at VSS2011, that some common properties perceivable from images of fabrics can be altered by increasing or decreasing the relative energy in specific spatial-frequency bands of the amplitude spectra. This result suggests that simple neural "detectors" for material properties could just combine the outputs of sets of V1 frequency-selective neurons. Can such detectors be revealed through selective adaptation? If observers adapt to a specific frequency-band, thus shifting the balance of sensitivities to other parts of the spectrum, does that shift their judgment of the associated material property? Using frequency-bands identified by our image analyses, we answer these questions for the fabric properties of volume, roughness, and thickness. For test stimuli, we used images of fabrics, along with two versions of each image with increased relative energy in the specific frequency band (constant total energy), and two with decreased relative energy. Baseline psychometric functions for each property were measured by comparing the original image side-by-side with its manipulated or unaltered version. During adaptation, bandpass-filtered dynamic white noise patches were presented on the location of the original image, and complementary notch-filtered dynamic noise patches on the location of the comparison images. The post-adaptation psychometric curve was measured by interleaving adaptation and test presentations. As predicted for each adaptation frequency-band, observers judged fabrics as having systematically less surface volume, softer texture, or thinner weave/knit than the original percept. The results demonstrate that observers directly use broad-band spatial frequency information in perceiving material properties, and suggest that V1 neurons transmit spatial-frequency signals in parallel for material perception.
Meeting abstract presented at VSS 2012
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