September 2019
Volume 19, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2019
Haptic-visual crossmodal shape matching
Author Affiliations & Notes
  • Farley Norman
    Department of Psychological Sciences, Ogden College of Science and Engineering, Western Kentucky University
  • Sydney P Wheeler
    Carol Martin Gatton Academy of Mathematics and Science
  • Lauren E Pedersen
    Department of Psychological Sciences, Ogden College of Science and Engineering, Western Kentucky University
Journal of Vision September 2019, Vol.19, 198b. doi:https://doi.org/10.1167/19.10.198b
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    • Get Citation

      Farley Norman, Sydney P Wheeler, Lauren E Pedersen; Haptic-visual crossmodal shape matching. Journal of Vision 2019;19(10):198b. doi: https://doi.org/10.1167/19.10.198b.

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

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Abstract

A set of two experiments evaluated the crossmodal perception of solid shape. Sixty-six total participants (mean age = 21.2 years) haptically explored a single randomly-selected object on each trial and then indicated which of 12 visible objects possessed the same shape. Three different types of objects were used, two of which possessed natural shapes (bell peppers & sweet potatoes: Capsicum annuum and Ipomoea batatas, respectively), while the third object type was a set of sinusoidally-modulated spheres (SIMS, see Norman, Todd, & Phillips, 1995). Each object was haptically explored with both hands for 7 seconds. Even though the particular object shapes within each object type were mathematically distinct and unique, the participants’ crossmodal matching accuracies varied substantially (F(2, 63) = 128.6, p < .000001, partial eta squared = .80) across the object types (78.7, 60.9, & 18.6 percent correct for sweet potatoes, bell peppers, and sinusoidally-modulated spheres, respectively). The naturally-shaped objects (bell peppers & sweet potatoes) were much more identifiable to vision and haptics, because their distributions of distinctly shaped surface regions (areas of differing Gaussian curvature; e.g., convex or concave hemispherical regions, saddle-shaped regions, cylindrical regions) were heterogeneous. In contrast, the randomly-shaped SIMS were substantially less identifiable, because their distributions of distinctly shaped surface regions were much more homogeneous. The results of the current study document what variations in surface shape produce objects that are highly recognizable to human vision and haptics.

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