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dc.contributor.authorGuo, Crystal
dc.date.accessioned2022-06-14T15:18:32Z
dc.date.available2022-06-14T15:18:32Z
dc.date.issued2022-06-13
dc.identifier.urihttp://hdl.handle.net/20.500.12648/7327
dc.description.abstractBiological visual systems rely on pose estimation of three-dimensional (3D) objects to understand and navigate the surrounding environment, but the neural computations and mechanisms for inferring 3D poses from 2D retinal images are only partially understood, especially for conditions where stereo information is insufficient. We previously presented evidence that humans use the geometrical back-transform from retinal images to infer the poses of 3D objects lying centered on the ground. This model explained the almost veridical estimation of poses in real scenes and the illusory rotation of poses in obliquely viewed pictures, including the pointing at you phenomenon. Here we test this model for 3D objects in more varied configurations and find that it needs to be augmented. Five observers estimated poses of inclined, floating, or off-center 3D sticks in each of 16 different poses displayed on a monitor viewed straight or obliquely. Pose estimates in scenes and pictures showed remarkable accuracy and agreement between observers, but with a systematic fronto-parallel bias for oblique poses. When one end of an object is on the ground while the other is inclined up, the projected retinal orientation changes substantially as a function of inclination, so the back-transform derived from the object’s projection to the retina is not unique unless the angle of inclination is known. We show that observers’ pose estimates can be explained by the back-transform from retinal orientation only if it is derived for close to the correct inclination. The same back-transform explanation applies to obliquely viewed pictures. There is less change in retinal orientations when objects are floated or placed off-center but pose estimates can be explained by the same model, making it more likely that observers use internalized perspective geometry to make 3D pose inferences while actively incorporating inferences about other aspects of object placement.en_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectPose estimationen_US
dc.subjectRetinal orientationen_US
dc.subjectProjective geometryen_US
dc.subjectPicture perceptionen_US
dc.titleComplexity of mental geometry for 3D pose perceptionen_US
dc.typeMasters Thesisen_US
dc.description.versionNAen_US
refterms.dateFOA2022-06-14T15:18:32Z
dc.description.institutionSUNY College of Optometryen_US
dc.description.degreelevelMSen_US


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Attribution-NonCommercial-NoDerivatives 4.0 International
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International