User-defined interface gestures : dataset and analysis
Abstract
We 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.
Citation
Grijincu , 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 . DOI: 10.1145/2669485.2669511
Publication
Proceedings of the 9th ACM International Conference on Interactive Tabletops and Surfaces (ITS 2014)
Type
Conference item
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/10.1145/2669485.2669511 This 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.
Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
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