December 2022
Volume 22, Issue 14
Open Access
Vision Sciences Society Annual Meeting Abstract  |   December 2022
Inferring shape transformations in a drawing task
Author Affiliations & Notes
  • Filipp Schmidt
    Justus Liebig University Giessen
    Center for Mind, Brain and Behavior (CMBB), Marburg and Giessen
  • Henning Tiedemann
    Justus Liebig University Giessen
  • Roland W. Fleming
    Justus Liebig University Giessen
  • Yaniv Morgenstern
    Justus Liebig University Giessen
    Center for Mind, Brain and Behavior (CMBB), Marburg and Giessen
  • Footnotes
    Acknowledgements  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)–project number 222641018–SFB/TRR 135 TP C1; European Research Council (ERC) Consolidator Award ‘SHAPE’–project number ERC-CoG-2015-682859; Hessian Ministry of Higher Education, Research and the Arts–cluster project “The Adaptive Mind”
Journal of Vision December 2022, Vol.22, 3329. doi:
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    • Get Citation

      Filipp Schmidt, Henning Tiedemann, Roland W. Fleming, Yaniv Morgenstern; Inferring shape transformations in a drawing task. Journal of Vision 2022;22(14):3329.

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

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Many objects and materials in our environment are subject to transformations that alter their shape. For example, branches bend in the wind, ice melts, paper crumples, and wood is often carved. Still, we recognize objects and materials across these changes, suggesting we can distinguish an object’s original features from those caused by the transformations (“shape scission”). Yet, to truly understand transformations, we should not only be able to identify their signatures in an observed object, but also actively apply the transformation to new objects (i.e., through imagination or mental simulation). On a tablet computer, participants viewed a base contour and its transformed version, and were asked to apply the same transformation to a test contour by drawing what the transformed test shape should look like. Thus, to perform the task, observers had to (i) infer the transformation from the shape differences between the base contours, (ii) apply it to the test contour (through visual imagery), and (iii) draw the result. Our findings show that overall observers’ drawings are more similar to the ground truth transformed test shape than to the original test shape or the transformed base shape — demonstrating that they can indeed infer and reproduce transformations from observation. This ability is strongly modulated by the type of transformation, and also by the similarity between base and test contours, but not by the transformation magnitudes. Furthermore, observers’ strategies were consistent with a model that applied a transformation vector field between the original and transformed base shapes to the test shapes. Together, our findings suggest that we can distinguish between representations of original object shapes and their transformations, and can use visual imagery to mentally apply nonrigid transformations to observed objects. Such abilities are an important aspect of how we not only perceive but also ‘understand’ shape.


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