Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/34962
Appears in Collections:Psychology Journal Articles
Peer Review Status: Refereed
Title: Luminance contrast provides metric depth information
Author(s): Hibbard, Paul
Goutcher, Ross
Hornsey, Rebecca
Hunter, David
Scarfe, Peter
Contact Email: ross.goutcher@stir.ac.uk
Keywords: stereopsis
vision
binocular disparity
shape from shading
image statistics
Issue Date: Feb-2023
Date Deposited: 8-Mar-2023
Citation: Hibbard P, Goutcher R, Hornsey R, Hunter D & Scarfe P (2023) Luminance contrast provides metric depth information. <i>Royal Society Open Science</i>, 10 (2), Art. No.: 220567. https://doi.org/10.1098/rsos.220567
Abstract: The perception of depth from retinal images depends on information from multiple visual cues. One potential depth cue is the statistical relationship between luminance and distance; darker points in a local region of an image tend to be farther away than brighter points. We establish that this statistical relationship acts as a quantitative cue to depth. We show that luminance variations affect depth in naturalistic scenes containing multiple cues to depth. This occurred when the correlation between variations of luminance and depth was manipulated within an object, but not between objects. This is consistent with the local nature of the statistical relationship in natural scenes. We also showed that perceived depth increases as contrast is increased, but only when the depth signalled by luminance and binocular disparity are consistent. Our results show that the negative correlation between luminance and distance, as found under diffuse lighting, provides a depth cue that is combined with depth from binocular disparity, in a way that is consistent with the simultaneous estimation of surface depth and reflectance variations. Adopting more complex lighting models such as ambient occlusion in computer rendering will thus contribute to the accuracy as well as the aesthetic appearance of three-dimensional graphics.
DOI Link: 10.1098/rsos.220567
Rights: © 2023 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited
Licence URL(s): http://creativecommons.org/licenses/by/4.0/

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