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dc.contributor.authorShih, YiChang
dc.contributor.authorDavis, Abe
dc.contributor.authorHasinoff, Samuel W.
dc.contributor.authorDurand, Fredo
dc.contributor.authorFreeman, William T.
dc.date.accessioned2014-05-05T16:31:28Z
dc.date.available2014-05-05T16:31:28Z
dc.date.issued2012-06
dc.identifier.isbn978-1-4673-1228-8
dc.identifier.isbn978-1-4673-1226-4
dc.identifier.isbn978-1-4673-1227-1
dc.identifier.urihttp://hdl.handle.net/1721.1/86407
dc.description.abstractIt is often desirable to detect whether a surface has been touched, even when the changes made to that surface are too subtle to see in a pair of before and after images. To address this challenge, we introduce a new imaging technique that combines computational photography and laser speckle imaging. Without requiring controlled laboratory conditions, our method is able to detect surface changes that would be indistinguishable in regular photographs. It is also mobile and does not need to be present at the time of contact with the surface, making it well suited for applications where the surface of interest cannot be constantly monitored. Our approach takes advantage of the fact that tiny surface deformations cause phase changes in reflected coherent light which alter the speckle pattern visible under laser illumination. We take before and after images of the surface under laser light and can detect subtle contact by correlating the speckle patterns in these images. A key challenge we address is that speckle imaging is very sensitive to the location of the camera, so removing and reintroducing the camera requires high-accuracy viewpoint alignment. To this end, we use a combination of computational rephotography and correlation analysis of the speckle pattern as a function of camera translation. Our technique provides a reliable way of detecting subtle surface contact at a level that was previously only possible under laboratory conditions. With our system, the detection of these subtle surface changes can now be brought into the wild.en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (CGV 1111415)en_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/CVPR.2012.6247655en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT web domainen_US
dc.titleLaser speckle photography for surface tampering detectionen_US
dc.typeArticleen_US
dc.identifier.citationYi Chang Shih, A. Davis, S. W. Hasinoff, F. Durand, and W. T. Freeman. “Laser Speckle Photography for Surface Tampering Detection.” 2012 IEEE Conference on Computer Vision and Pattern Recognition (n.d.).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.contributor.mitauthorShih, YiChangen_US
dc.contributor.mitauthorDavis, Abeen_US
dc.contributor.mitauthorHasinoff, Samuel W.en_US
dc.contributor.mitauthorDurand, Fredoen_US
dc.contributor.mitauthorFreeman, William T.en_US
dc.relation.journalProceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognitionen_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
dspace.orderedauthorsYi Chang Shih; Davis, A.; Hasinoff, S. W.; Durand, F.; Freeman, W. T.en_US
dc.identifier.orcidhttps://orcid.org/0000-0003-1469-2696
dc.identifier.orcidhttps://orcid.org/0000-0001-9919-069X
dc.identifier.orcidhttps://orcid.org/0000-0002-2231-7995
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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