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dc.contributor.authorSong, Yale
dc.contributor.authorDemirdjian, David
dc.contributor.authorDavis, Randall
dc.date.accessioned2013-06-26T16:40:10Z
dc.date.available2013-06-26T16:40:10Z
dc.date.issued2011-03
dc.identifier.isbn978-1-4244-9140-7
dc.identifier.otherINSPEC Accession Number: 12007776
dc.identifier.urihttp://hdl.handle.net/1721.1/79376
dc.description.abstractWe present a unified framework for body and hand tracking, the output of which can be used for understanding simultaneously performed body-and-hand gestures. The framework uses a stereo camera to collect 3D images, and tracks body and hand together, combining various existing techniques to make tracking tasks efficient. In addition, we introduce a multi-signal gesture database: the NATOPS aircraft handling signals. Unlike previous gesture databases, this data requires knowledge about both body and hand in order to distinguish gestures. It is also focused on a clearly defined gesture vocabulary from a real-world scenario that has been refined over many years. The database includes 24 body-and-hand gestures, and provides both gesture video clips and the body and hand features we extracted.en_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/FG.2011.5771448en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike 3.0en_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/en_US
dc.sourceDavis via Amy Stouten_US
dc.titleTracking body and hands for gesture recognition: NATOPS aircraft handling signals databaseen_US
dc.typeArticleen_US
dc.identifier.citationSong, Yale, David Demirdjian, and Randall Davis. Tracking Body and Hands for Gesture Recognition: NATOPS Aircraft Handling Signals Database. In Face and Gesture 2011, 500-506. Institute of Electrical and Electronics Engineers, 2011.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorSong, Yaleen_US
dc.contributor.mitauthorDemirdjian, Daviden_US
dc.contributor.mitauthorDavis, Randallen_US
dc.relation.journalProceedings of the Automatic Face & Gesture Recognition and Workshops (FG 2011)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.orderedauthorsSong, Yale; Demirdjian, David; Davis, Randallen_US
dc.identifier.orcidhttps://orcid.org/0000-0001-5232-7281
mit.licenseOPEN_ACCESS_POLICYen_US


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