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Detecting the structural form of cast shadows patterns
Author(s) -
Sieu K. Khuu,
S. Khambiye,
Jack Phu
Publication year - 2012
Publication title -
journal of vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.126
H-Index - 113
ISSN - 1534-7362
DOI - 10.1167/12.11.10
Subject(s) - computer science
Cast shadows are ubiquitous in the visual scene and they inform greatly about the scene's three-dimensional spatial layout. In the present study we investigated the ability of the visual system to detect the structural form of cast shadows using Glass patterns consisting of local dot-pairs or dipoles oriented appropriately to convey global structure. "Cast shadow" Glass patterns were constructed by superimposing two opposite polarity (light-increment - the object - and light-decrement - the shadow) concentric Glass patterns and then spatially displacing the decrement pattern along a particular orientation conforming to the pattern's lighting direction. We determined the shadow detection threshold, which specifies the amount of structural difference between the object (increment Glass-pattern) and its respective shadow (decrement Glass-pattern), required for observers to detect the cast shadow. This was achieved by varying the ratio between local opposite-polarity dipole pairs that were appropriately aligned along the lighting direction (congruent dipole pairs), and dipole pairs that were randomly oriented (incongruent dipole pairs), and were therefore inconsistent with the pattern's lighting direction. We reported that thresholds were comparatively lower (i.e., the visual system is able to tolerate greater local pattern inconsistencies) for light-from-above patterns than for light-from-below patterns (Experiment 1), and detection is optimal for highly coherent patterns (Experiment 2) small spatial separations between opposite polarity (Experiment 3). Our findings demonstrated that the visual system is more sensitive to light-from-above configurations when detecting the form of cast shadows, and this detection process largely ignores local inconsistencies between the object and its respective shadow.

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