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dc.contributor.authorNoraky, James
dc.contributor.authorSze, Vivienne
dc.date.accessioned2018-12-03T19:02:28Z
dc.date.available2018-12-03T19:02:28Z
dc.date.issued2018-10
dc.identifier.isbn978-1-4673-9961-6
dc.identifier.issn2381-8549
dc.identifier.urihttp://hdl.handle.net/1721.1/119397
dc.description.abstractDepth sensing is useful for a variety of applications that range from augmented reality to robotics. Time-of-flight (TOF) cameras are appealing because they obtain dense depth measurements with low latency. However, for reasons ranging from power constraints to multi-camera interference, the frequency at which accurate depth measurements can be obtained is reduced. To address this, we propose an algorithm that uses concurrently collected images to estimate the depth of non-rigid objects without using the TOF camera. Our technique models non-rigid objects as locally rigid and uses previous depth measurements along with the optical flow of the images to estimate depth. In particular, we show how we exploit the previous depth measurements to directly estimate pose and how we integrate this with our model to estimate the depth of non-rigid objects by finding the solution to a sparse linear system. We evaluate our technique on a RGB-D dataset of deformable objects, where we estimate depth with a mean relative error of 0.37% and outperform other adapted techniques.en_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceProf. Szeen_US
dc.titleDepth Estimation of Non-Rigid Objects For Time-Of-Flight Imagingen_US
dc.typeArticleen_US
dc.identifier.citationNoraky, James and Vivienne Sze. "Depth Estimation of Non-Rigid Objects For Time-Of-Flight Imaging." ICIP 2018: 2925-2929.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Microsystems Technology Laboratoriesen_US
dc.contributor.approverSze, Vivienneen_US
dc.contributor.mitauthorNoraky, James
dc.contributor.mitauthorSze, Vivienne
dc.relation.journalIEEE International Conference on Image Processing (ICIP)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.orderedauthorsNoraky, James; Sze, Vivienneen_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0001-8552-7458
dc.identifier.orcidhttps://orcid.org/0000-0003-4841-3990
mit.licenseOPEN_ACCESS_POLICYen_US


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