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dc.contributor.authorBaradad, Manel
dc.contributor.authorYe, Vickie
dc.contributor.authorYedidia, Adam B.
dc.contributor.authorDurand, Fredo
dc.contributor.authorFreeman, William T
dc.contributor.authorWornell, Gregory W
dc.contributor.authorTorralba, Antonio
dc.date.accessioned2021-11-15T17:00:36Z
dc.date.available2021-11-04T19:10:29Z
dc.date.available2021-11-04T19:11:42Z
dc.date.available2021-11-15T17:00:36Z
dc.date.issued2018-06
dc.identifier.urihttps://hdl.handle.net/1721.1/137399.3
dc.description.abstract© 2018 IEEE. We present a method for inferring a 4D light field of a hidden scene from 2D shadows cast by a known occluder on a diffuse wall. We do this by determining how light naturally reflected off surfaces in the hidden scene interacts with the occluder. By modeling the light transport as a linear system, and incorporating prior knowledge about light field structures, we can invert the system to recover the hidden scene. We demonstrate results of our inference method across simulations and experiments with different types of occluders. For instance, using the shadow cast by a real house plant, we are able to recover low resolution light fields with different levels of texture and parallax complexity. We provide two experimental results: A human subject and two planar elements at different depths.en_US
dc.description.sponsorshipDARPA (Contract HR0011-16-C-0030)en_US
dc.language.isoen
dc.publisherIEEEen_US
dc.relation.isversionof10.1109/cvpr.2018.00656en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceComputer Vision Foundationen_US
dc.titleInferring Light Fields from Shadowsen_US
dc.typeArticleen_US
dc.identifier.citation"Inferring Light Fields from Shadows."en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-05-28T13:22:22Z
dspace.date.submission2019-05-28T13:22:23Z
mit.metadata.statusPublication Information Neededen_US


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