Performance data indicate summation for pictorial depth-cues in slanted surfaces

Timothy S. Meese*, D.J. Holmes

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Over recent years much has been learned about the way in which depth cues are combined (e.g. Landy et al., 1995). The majority of this work has used subjective measures, a rating scale or a point of subjective equality, to deduce the relative contributions of different cues to perception. We have adopted a very different approach by using two interval forced-choice (2IFC) performance measures and a signal processing framework. We performed summation experiments for depth cue increment thresholds between pairs of pictorial depth cues in displays depicting slanted planar surfaces made from arrays of circular 'contrast' elements. Summation was found to be ideal when size-gradient was paired with contrast-gradient for a wide range of depth-gradient magnitudes in the null stimulus. For a pairing of size-gradient and linear perspective, substantial summation (> 1.5 dB) was found only when the null stimulus had intermediate depth gradients; when flat or steeply inclined surfaces were depicted, summation was diminished or abolished. Summation was also abolished when one of the target cues was (i) not a depth cue, or (ii) added in conflict. We conclude that vision has a depth mechanism for the constructive combination of pictorial depth cues and suggest two generic models of summation to describe the results. Using similar psychophysical methods, Bradshaw and Rogers (1996) revealed a mechanism for the depth cues of motion parallax and binocular disparity. Whether this is the same or a different mechanism from the one reported here awaits elaboration.

Original languageEnglish
Pages (from-to)127-151
Number of pages25
JournalSpatial vision
Volume17
Issue number1-2
DOIs
Publication statusPublished - 5 Apr 2004

Bibliographical note

Annual Conference of the Applied-Vision-Association, London (UK, 20 March 2001.

Keywords

  • contrast
  • discrimination
  • gradient
  • size
  • texture
  • vision

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