dc.contributor.author | Rhemann, Christoph | |
dc.contributor.author | Izadi, Shahram | |
dc.contributor.author | Sing Bing Kang, Ramesh | |
dc.contributor.author | Naik, Nikhil Deepak | |
dc.contributor.author | Kadambi, Achuta | |
dc.contributor.author | Raskar, Ramesh | |
dc.date.accessioned | 2017-07-11T17:56:55Z | |
dc.date.available | 2017-07-11T17:56:55Z | |
dc.date.issued | 2015-10 | |
dc.date.submitted | 2015-06 | |
dc.identifier.isbn | 978-1-4673-6964-0 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/110641 | |
dc.description.abstract | Continuous-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.iso | en_US | |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1109/CVPR.2015.7298602 | en_US |
dc.rights | Creative Commons Attribution-Noncommercial-Share Alike | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en_US |
dc.source | MIT web domain | en_US |
dc.title | A light transport model for mitigating multipath interference in Time-of-flight sensors | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Naik, 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.department | Massachusetts Institute of Technology. Media Laboratory | en_US |
dc.contributor.department | Program in Media Arts and Sciences (Massachusetts Institute of Technology) | en_US |
dc.contributor.mitauthor | Naik, Nikhil Deepak | |
dc.contributor.mitauthor | Kadambi, Achuta | |
dc.contributor.mitauthor | Raskar, Ramesh | |
dc.relation.journal | 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
eprint.status | http://purl.org/eprint/status/NonPeerReviewed | en_US |
dspace.orderedauthors | Naik, Nikhil; Kadambi, Achuta; Rhemann, Christoph; Izadi, Shahram; Raskar, Ramesh; Sing Bing Kang, Ramesh | en_US |
dspace.embargo.terms | N | en_US |
dc.identifier.orcid | https://orcid.org/0000-0002-9894-8865 | |
dc.identifier.orcid | https://orcid.org/0000-0002-3254-3224 | |
mit.license | OPEN_ACCESS_POLICY | en_US |