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dc.contributor.authorGrijincu, Daniela
dc.contributor.authorNacenta, Miguel
dc.contributor.authorKristensson, Per Ola
dc.date.accessioned2014-11-28T10:02:26Z
dc.date.available2014-11-28T10:02:26Z
dc.date.issued2014-11-16
dc.identifier.citationGrijincu , D , Nacenta , M & Kristensson , P O 2014 , User-defined interface gestures : dataset and analysis . in Proceedings of the 9th ACM International Conference on Interactive Tabletops and Surfaces (ITS 2014) . ACM , New York, NY , pp. 25-34 . https://doi.org/10.1145/2669485.2669511en
dc.identifier.isbn9781450325875
dc.identifier.otherPURE: 152716174
dc.identifier.otherPURE UUID: 5f9ce4c1-ccc4-4018-9e40-18ec37489402
dc.identifier.otherScopus: 84919340632
dc.identifier.otherORCID: /0000-0002-9864-9654/work/34034535
dc.identifier.urihttps://hdl.handle.net/10023/5841
dc.description.abstractWe present a video-based gesture dataset and a methodology for annotating video-based gesture datasets. Our dataset consists of user-defined gestures generated by 18 participants from a previous investigation of gesture memorability. We design and use a crowd-sourced classification task to annotate the videos. The results are made available through a web-based visualization that allows researchers and designers to explore the dataset. Finally, we perform an additional descriptive analysis and quantitative modeling exercise that provide additional insights into the results of the original study. To facilitate the use of the presented methodology by other researchers we share the data, the source of the human intelligence tasks for crowdsourcing, a new taxonomy that integrates previous work, and the source code of the visualization tool.
dc.format.extent10
dc.language.isoeng
dc.publisherACM
dc.relation.ispartofProceedings of the 9th ACM International Conference on Interactive Tabletops and Surfaces (ITS 2014)en
dc.rights© Authors/owners 2014. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in the Proceedings of the 2014 ACM Interactive Tabletops and Surfaces Conference (ITS '14), http://dx.doi.org/10.1145/2669485.2669511 The copy of record of the paper can be found in: http://dx.doi.org/10.1145/2669485.2669511en
dc.rightsThis material is open for use by anyone. We would appreciate if you cite the original paper if you use the data or the videos in your own work.en
dc.subjectGesture designen
dc.subjectUser-defined gesturesen
dc.subjectGesture elicitationen
dc.subjectGesture analysis methodologyen
dc.subjectGesture annotationen
dc.subjectGesture memorabilityen
dc.subjectGesturesen
dc.subjectGesture datasetsen
dc.subjectCrowdsourcingen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subject.lccQA75en
dc.titleUser-defined interface gestures : dataset and analysisen
dc.typeConference itemen
dc.description.versionPostprinten
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews. School of Computer Scienceen
dc.identifier.doihttps://doi.org/10.1145/2669485.2669511
dc.date.embargoedUntil2014-11-10
dc.identifier.urlhttp://udigesturesdataset.cs.st-andrews.ac.uk/en


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