Specular reflections and the estimation of shape from binocular disparity

A.A. Muryy, A.E. Welchman, A. Blake, R.W. Fleming

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)
166 Downloads (Pure)

Abstract

Binocular stereopsis is a powerful visual depth cue. To exploit it, the brain matches features from the two eyes' views and measures their interocular disparity. This works well for matte surfaces because disparities indicate true surface locations. However, specular (glossy) surfaces are problematic because highlights and reflections are displaced from the true surface in depth, leading to information that conflicts with other cues to 3D shape. Here, we address the question of how the visual system identifies the disparity information created by specular reflections. One possibility is that the brain uses monocular cues to identify that a surface is specular and modifies its interpretation of the disparities accordingly. However, by characterizing the behavior of specular disparities we show that the disparity signals themselves provide key information ("intrinsic markers") that enable potentially misleading disparities to be identified and rejected. We presented participants with binocular views of specular objects and asked them to report perceived depths by adjusting probe dots. For simple surfaces-which do not exhibit intrinsic indicators that the disparities are "wrong"-participants incorrectly treat disparities at face value, leading to erroneous judgments. When surfaces are more complex we find the visual system also errs where the signals are reliable, but rejects and interpolates across areas with large vertical disparities and horizontal disparity gradients. This suggests a general mechanism in which the visual system assesses the origin and utility of sensory signals based on intrinsic markers of their reliability.
Original languageEnglish
Pages (from-to)2413-2418
Number of pages6
JournalNational Academy of Sciences. Proceedings
Volume110
Issue number6
Early online date22 Jan 2013
DOIs
Publication statusPublished - 5 Feb 2013

Keywords

  • psychophysics
  • perception
  • gloss
  • texture
  • computational analysis

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