August 2014
Volume 14, Issue 10
Free
Vision Sciences Society Annual Meeting Abstract  |   August 2014
Closure and global shape contributions to contour grouping
Author Affiliations
  • Ingo Fründ
    Center for Vision Research, York University, Toronto, ON, Canada
  • James H Elder
    Center for Vision Research, York University, Toronto, ON, Canada
Journal of Vision August 2014, Vol.14, 257. doi:10.1167/14.10.257
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      Ingo Fründ, James H Elder; Closure and global shape contributions to contour grouping . Journal of Vision 2014;14(10):257. doi: 10.1167/14.10.257.

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

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Abstract

Perceptual organization of natural scenes is effortless and immediate despite fragmentation and obscuration of object boundaries caused by occlusions and clutter. The standard model for boundary grouping is based upon an 'association field' that governs local grouping, and a Markov or transitivity assumption that allows global contours to be inferred solely from local properties. Psychophysical 'path detection' experiments have revealed sensitivity to local geometry consistent with this association field hypothesis. Recently, however, it has been shown that detection of natural animal shapes is more efficient than detection of 'metamer' contours that match the natural contours in their local geometry but contain no global regularities (Elder et al, 2010, J Vis, 10(7):1171). This suggests that global shape also plays a role in contour grouping. Yet, since these metamer controls are open contours, the findings may derive purely from the closure of the natural shapes. To address this issue, we employ a novel MCMC methodology (Fründ & Elder, 2013, J Vis, 13(9):119) to produce closed metamer contours, statistically matched in their local geometry to natural animal shapes, but otherwise maximum entropy, containing no global regularities beyond closure. We conducted path detection experiments using these 3 stimuli (open metamers, closed metamers, natural shapes) at different contour sampling rates (number of elements per contour), and estimated noise threshold for criterion performance. At low sampling rates, performance was similar for the three conditions. However, as sampling rate was increased to 20 elements per contour, performance for natural shapes and closed metamers exceeded performance for open metamers (t(7)>2.4, p<0.04), and at 40 elements, performance for natural shapes exceeded performance for closed metamers (t(10)=2.6, p=0.02). These results show that the visual system exploits both closure and additional global properties of natural shape in the segmentation of bounding contours from cluttered scenes, challenging purely local accounts of contour grouping.

Meeting abstract presented at VSS 2014

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