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Chien-Chung Chen, Christopher Tyler; Perceived depth from luminance gradient and disparity. Journal of Vision 2013;13(9):262. doi: https://doi.org/10.1167/13.9.262.
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© ARVO (1962-2015); The Authors (2016-present)
Perceived depth is conveyed by multiple cues, including binocular disparity and luminance shading. Depth perception from 3D-shape-from-shading information depends on the perceptual assumption of the incident light, which has been shown to default to a diffuse illumination assumption (Tyler, 1998, J Inf Sci Tech, 42:319-25). We ask how shading and disparity cues combine for surfaces defined by the joint luminance and disparity modulation of textured sinusoidal luminance gratings. The observers’ task was to adjust the binocular disparity of a comparison random-dot stereogram (uniform dot distribution, dot size 2’) to match the perceived depth of a target consisting of the sum of a disparity-modulated sinusoidal luminance modulation (0.5 or 2 cyc/deg, contrast 20%-80%) target and a random dot pattern (contrast 0%-20%) to simulate surface texture and to enhance disparity information in the target stimuli. The target disparity was modulated from 0’-20’ and was either in-phase or in opposite phase with the luminance modulation. Five observers participated. Regardless target spatial frequency, when texture contrast was low (or zero), the perceived target depth increased with the luminance contrast and the perceived concaveness depended on luminance phase but was not affected by the luminance disparity modulation. At high texture contrast, the perceived depth modulation increased linearly with target disparity modulation but was not affected by target contrast. These results validate the idea that a human observer can use the diffuse illumination assumption to perceive depth from luminance gradients alone without making the assumption of light direction. With combined cues, the observer used EITHER luminance shading OR disparity for depth judgment but not both. Such all-or-none behavior suggests that disjunctive mechanisms underlie these two types of information.
Meeting abstract presented at VSS 2013
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