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Nicole Wong, Dorita Chang; The effects of object plausibility on disparity perception. Journal of Vision 2018;18(10):994. doi: 10.1167/18.10.994.
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© ARVO (1962-2015); The Authors (2016-present)
Binocular disparity is one of the most important cues for retrieving depth from object structures. However, little is known as to the mechanisms underlying disparity-based depth processing under complex contexts. In two experiments, we asked how the plausibility of complex 3D objects, as dictated by the conformity of the stimulus with natural physical laws, affects the retrieval of disparity information. Stimuli were disparity-defined 3D objects (triangle and cube) rendered as random dot stereograms (RDS). Stimuli were presented in possible and impossible variations (e.g., a normal versus a Penrose triangle). Observers were asked to complete both a signal-noise task, judging whether the object was in front or behind of a reference plane, and a feature discrimination task, judging which of two consecutively presented targets was nearer. Task difficulty was manipulated via the QUEST staircase procedure. We varied the percentage of signal dots laying on versus off of the object surface (SNR task), or the disparity difference (1-150 arcsecs) between the objects presented in the two intervals (feature task). Interestingly, results showed greater sensitivities of SNR-based depth judgments for impossible versus possible objects. We observed a subtler advantage for judging depth of impossible objects in the feature task. Our data suggest that disparity representations may be modulated by higher order contextual information, signalling an intrinsic relationship between object and disparity processing.
Meeting abstract presented at VSS 2018
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