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dc.contributor.authorRhemann, Christoph
dc.contributor.authorIzadi, Shahram
dc.contributor.authorSing Bing Kang, Ramesh
dc.contributor.authorNaik, Nikhil Deepak
dc.contributor.authorKadambi, Achuta
dc.contributor.authorRaskar, Ramesh
dc.date.accessioned2017-07-11T17:56:55Z
dc.date.available2017-07-11T17:56:55Z
dc.date.issued2015-10
dc.date.submitted2015-06
dc.identifier.isbn978-1-4673-6964-0
dc.identifier.urihttp://hdl.handle.net/1721.1/110641
dc.description.abstractContinuous-wave Time-of-flight (TOF) range imaging has become a commercially viable technology with many applications in computer vision and graphics. However, the depth images obtained from TOF cameras contain scene dependent errors due to multipath interference (MPI). Specifically, MPI occurs when multiple optical reflections return to a single spatial location on the imaging sensor. Many prior approaches to rectifying MPI rely on sparsity in optical reflections, which is an extreme simplification. In this paper, we correct MPI by combining the standard measurements from a TOF camera with information from direct and global light transport. We report results on both simulated experiments and physical experiments (using the Kinect sensor). Our results, evaluated against ground truth, demonstrate a quantitative improvement in depth accuracy.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.2015.7298602en_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.titleA light transport model for mitigating multipath interference in Time-of-flight sensorsen_US
dc.typeArticleen_US
dc.identifier.citationNaik, Nikhil et al. “A Light Transport Model for Mitigating Multipath Interference in Time-of-Flight Sensors.” 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 7-12 June, 2015, Boston, Massachusetts, USA, IEEE, 2015.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Media Laboratoryen_US
dc.contributor.departmentProgram in Media Arts and Sciences (Massachusetts Institute of Technology)en_US
dc.contributor.mitauthorNaik, Nikhil Deepak
dc.contributor.mitauthorKadambi, Achuta
dc.contributor.mitauthorRaskar, Ramesh
dc.relation.journal2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)en_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.orderedauthorsNaik, Nikhil; Kadambi, Achuta; Rhemann, Christoph; Izadi, Shahram; Raskar, Ramesh; Sing Bing Kang, Rameshen_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-9894-8865
dc.identifier.orcidhttps://orcid.org/0000-0002-3254-3224
mit.licenseOPEN_ACCESS_POLICYen_US


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