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dc.contributor.authorAdelson, Edward H.
dc.contributor.authorJohnson, Micah K.
dc.date.accessioned2010-10-20T15:46:35Z
dc.date.available2010-10-20T15:46:35Z
dc.date.issued2009-08
dc.date.submitted2009-06
dc.identifier.isbn978-1-4244-3992-8
dc.identifier.issn1063-6919
dc.identifier.otherINSPEC Accession Number: 10836095
dc.identifier.urihttp://hdl.handle.net/1721.1/59425
dc.description.abstractWe describe a novel device that can be used as a 2.5D "scanner" for acquiring surface texture and shape. The device consists of a slab of clear elastomer covered with a reflective skin. When an object presses on the skin, the skin distorts to take on the shape of the object's surface. When viewed from behind (through the elastomer slab), the skin appears as a relief replica of the surface. A camera records an image of this relief, using illumination from red, green, and blue light sources at three different positions. A photometric stereo algorithm that is tailored to the device is then used to reconstruct the surface. There is no problem dealing with transparent or specular materials because the skin supplies its own BRDF. Complete information is recorded in a single frame; therefore we can record video of the changing deformation of the skin, and then generate an animation of the changing surface. Our sensor has no moving parts (other than the elastomer slab), uses inexpensive materials, and can be made into a portable device that can be used "in the field" to record surface shape and texture.en_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/CVPRW.2009.5206534en_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.sourceIEEEen_US
dc.titleRetrographic sensing for the measurement of surface texture and shapeen_US
dc.typeArticleen_US
dc.identifier.citationJohnson, M.K., and E.H. Adelson. “Retrographic sensing for the measurement of surface texture and shape.” Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on. 2009. 1070-1077. © 2009Institute of Electrical and Electronics Engineers.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.contributor.approverAdelson, Edward H.
dc.contributor.mitauthorAdelson, Edward H.
dc.contributor.mitauthorJohnson, Micah K.
dc.relation.journalIEEE Conference on Computer Vision and Pattern Recognition, 2009. CVPR 2009en_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsJohnson, M.K.; Adelson, E.H.en
dc.identifier.orcidhttps://orcid.org/0000-0003-2222-6775
mit.licensePUBLISHER_POLICYen_US
mit.metadata.statusComplete


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