Skeletal representations of shape in human vision: Evidence for a pruned medial axis model

• Type of Material: Article
• Authors: Valdislav Ayzenberg, Emory University; Yunxiao Chen, London School of Economics and Political Science; Sami R. Yousif, Yale University; Stella F. Lourenco, Emory University
• Language: English
• Date: 2019-06-27
• Publisher: ARVO
• Publication Version: Final Published Version
• Copyright Statement: © 2019 The Authors
• License: Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International
• Final Published Version (URL): https://doi.org/10.1167/19.6.6
• Title of Journal or Parent Work: Journal of Vision
• Volume: 19
• Issue: 6
• Start Page: 6
• Grant/Funding Agency: NAEd/Spencer Postdoctoral Fellowship; National Institutes of Health; Emory University
• Grant/Funding Information: This work was supported by a National Institutes of Health (NIH) institutional training grant (T32 HD071845) awarded to VA, a NAEd/Spencer Postdoctoral Fellowship awarded to YC, a National Science Foundation (NSF) Graduate Research Fellowship (GRFP) awarded to SRY, and a grant from the Program to Enhance Research and Scholarship (PERS) at Emory University awarded to SFL.
• Keywords: visual perception; pruning; computation; shape skeleton; medial axis
• Subject - Topics: Visual perception; Computational neuroscience; Computer vision

Abstract

A representation of shape that is low dimensional and stable across minor disruptions is critical for object recognition. Computer vision research suggests that such a representation can be supported by the medial axis—a computational model for extracting a shape's internal skeleton. However, few studies have shown evidence of medial axis processing in humans, and even fewer have examined how the medial axis is extracted in the presence of disruptive contours. Here, we tested whether human skeletal representations of shape reflect the medial axis transform (MAT), a computation sensitive to all available contours, or a pruned medial axis, which ignores contours that may be considered “noise.” Across three experiments, participants (N = 2062) were shown complete, perturbed, or illusory two-dimensional shapes on a tablet computer and were asked to tap the shapes anywhere once. When directly compared with another viable model of shape perception (based on principal axes), participants' collective responses were better fit by the medial axis, and a direct test of boundary avoidance suggested that this result was not likely because of a task-specific cognitive strategy (Experiment 1). Moreover, participants' responses reflected a pruned computation in shapes with small or large internal or external perturbations (Experiment 2) and under conditions of illusory contours (Experiment 3). These findings extend previous work by suggesting that humans extract a relatively stable medial axis of shapes. A relatively stable skeletal representation, reflected by a pruned model, may be well equipped to support real-world shape perception and object recognition.