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Effect of Pictorial Depth Cues, Binocular Disparity Cues and Motion Parallax Depth Cues on Lightness Perception in Three-Dimensional Virtual Scenes

Public Library of Science
Publication Date
DOI: 10.1371/journal.pone.0003177
  • Research Article
  • Computational Biology/Computational Neuroscience
  • Neuroscience/Behavioral Neuroscience
  • Neuroscience/Experimental Psychology


Background Surface lightness perception is affected by scene interpretation. There is some experimental evidence that perceived lightness under bi-ocular viewing conditions is different from perceived lightness in actual scenes but there are also reports that viewing conditions have little or no effect on perceived color. We investigated how mixes of depth cues affect perception of lightness in three-dimensional rendered scenes containing strong gradients of illumination in depth. Methodology/Principal Findings Observers viewed a virtual room (4 m width×5 m height×17.5 m depth) with checkerboard walls and floor. In four conditions, the room was presented with or without binocular disparity (BD) depth cues and with or without motion parallax (MP) depth cues. In all conditions, observers were asked to adjust the luminance of a comparison surface to match the lightness of test surfaces placed at seven different depths (8.5–17.5 m) in the scene. We estimated lightness versus depth profiles in all four depth cue conditions. Even when observers had only pictorial depth cues (no MP, no BD), they partially but significantly discounted the illumination gradient in judging lightness. Adding either MP or BD led to significantly greater discounting and both cues together produced the greatest discounting. The effects of MP and BD were approximately additive. BD had greater influence at near distances than far. Conclusions/Significance These results suggest the surface lightness perception is modulated by three-dimensional perception/interpretation using pictorial, binocular-disparity, and motion-parallax cues additively. We propose a two-stage (2D and 3D) processing model for lightness perception.

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