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dc.contributor.authorDavis, Myers Abraham
dc.contributor.authorBouman, Katherine L.
dc.contributor.authorChen, Justin Gejune
dc.contributor.authorRubinstein, Michael
dc.contributor.authorDurand, Fredo
dc.contributor.authorFreeman, William T.
dc.date.accessioned2015-06-26T13:44:06Z
dc.date.available2015-06-26T13:44:06Z
dc.date.issued2015-06
dc.identifier.urihttp://hdl.handle.net/1721.1/97532
dc.description.abstractThe estimation of material properties is important for scene understanding, with many applications in vision, robotics, and structural engineering. This paper connects fundamentals of vibration mechanics with computer vision techniques in order to infer material properties from small, often imperceptible motion in video. Objects tend to vibrate in a set of preferred modes. The shapes and frequencies of these modes depend on the structure and material properties of an object. Focusing on the case where geometry is known or fixed, we show how information about an object’s modes of vibration can be extracted from video and used to make inferences about that object’s material properties. We demonstrate our approach by estimating material properties for a variety of rods and fabrics by passively observing their motion in high-speed and regular framerate video.en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Robust Intelligence 1212849 Reconstructive Recognition)en_US
dc.description.sponsorshipShell Oil Companyen_US
dc.description.sponsorshipQatar Computing Research Instituteen_US
dc.description.sponsorshipNational Science Foundation (U.S.). Graduate Research Fellowshipen_US
dc.language.isoen_US
dc.publisherComputer Vision Foundationen_US
dc.relation.isversionofhttp://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Davis_Visual_Vibrometry_Estimating_2015_CVPR_paper.pdfen_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceBoumanen_US
dc.titleVisual Vibrometry: Estimating Material Properties from Small Motions in Videoen_US
dc.typeArticleen_US
dc.identifier.citationDavis, Abe, Katherine L. Bouman, Justin G. Chen, Michael Rubinstein, Fredo Durand, and William T. Freeman. "Visual Vibrometry: Estimating Material Properties from Small Motions in Video." 2015 Computer Vision and Pattern Recognition Conference (June 2015).en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorDavis, Myers Abrahamen_US
dc.contributor.mitauthorBouman, Katherine L.en_US
dc.contributor.mitauthorChen, Justin Gejuneen_US
dc.contributor.mitauthorDurand, Fredoen_US
dc.contributor.mitauthorFreeman, William T.en_US
dc.relation.journalProceedings of the 2015 Computer Vision and Pattern Recognition Conferenceen_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.orderedauthorsDavis, Abe; Bouman, Katherine L.; Chen, Justin G.; Rubinstein, Michael; Durand, Fredo; Freeman, WIlliam T.en_US
dc.identifier.orcidhttps://orcid.org/0000-0003-1469-2696
dc.identifier.orcidhttps://orcid.org/0000-0001-5302-2463
dc.identifier.orcidhttps://orcid.org/0000-0001-9919-069X
dc.identifier.orcidhttps://orcid.org/0000-0002-2231-7995
dc.identifier.orcidhttps://orcid.org/0000-0003-0077-4367
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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