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major challenge for visual recognition is to describe shapes flexibly enough to allow generalization over different views. Computer vision models have championed a potential solution in medial-axis shape skeletons�hierarchically arranged geometric structures that are robust to deformations like bending and stretching. In the experiments reported here, we exploited an old, unheralded, and exceptionally simple paradigm to reveal the presence and nature of shape skeletons in human vision. When participants independently viewed a shape on a touch-sensitive tablet computer and simply tapped the shape anywhere they wished, the aggregated touches formed the shape�s medial-axis skeleton. This pattern held across several shape variations, demonstrating profound and predictable influences of even subtle border perturbations and amodally filled-in regions. This phenomenon reveals novel properties of shape representation and demonstrates (in an unusually direct way) how deep and otherwise-hidden visual processes can directly control simple behaviors, even while observers are completely unaware of their existence.
