October 2003
Volume 3, Issue 9
Vision Sciences Society Annual Meeting Abstract  |   October 2003
Shape categorization from texture
Author Affiliations
  • Victoria L Interrante
    Computer Science and Engineering, University of Minnesota, USA
Journal of Vision October 2003, Vol.3, 612. doi:https://doi.org/10.1167/3.9.612
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      Victoria L Interrante, Sunghee Kim, Haleh Hagh-Shenas; Shape categorization from texture. Journal of Vision 2003;3(9):612. https://doi.org/10.1167/3.9.612.

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      © ARVO (1962-2015); The Authors (2016-present)

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As computer science researchers, we are interested in gaining a better understanding of how to more effectively use texture to facilitate shape perception. To study these questions we have been using a novel texture synthesis algorithm to apply arbitrary patterns over arbitrary doubly curved surfaces in a way that avoids both seams and stretching yet allows fine control over the local texture orientation. Previously we found that judgments of shape from anisotropic textures are most accurate when the direction(s) of anisotropy are aligned with one or both of the principal directions over the surface. However many questions remain: why is it easier to accurately perceive the surface shape when the texture follows the principal directions? What information are we inferring from the texture orientation and how are we using it? How important is it that the pattern be capable of conveying the extent of texture compression along the principal directions in addition to or in lieu of directly indicating what these directions are? In our current experiments we are working with a disparate collection of 23 texture swatches, primarily drawn from the Brodatz album. We have applied these textures to families of quadric surface patches related by variations in curvature. We are showing subjects local views of the surfaces, in which no contour edges are visible. We have been struck by the strength of the influence of aperture shape cues on shape perception from texture at interior points. We are using two projection conditions: perspective and orthographic, and two viewing conditions: head-on and oblique. Each view is also rotated in the plane by a random angle. In a 4AFC task we are asking observers to classify the shapes as elliptic, hyperbolic, cylindrical or flat and then as convex, concave, both or neither. We are also asking them to indicate how they would grasp the object if they had to pinch it and lift it up.

Interrante, V. L., Kim, S., Hagh-Shenas, H.(2003). Shape categorization from texture [Abstract]. Journal of Vision, 3( 9): 612, 612a, http://journalofvision.org/3/9/612/, doi:10.1167/3.9.612. [CrossRef]

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