User-defined interface gestures: dataset and analysis

Daniela Grijincu; Miguel Nacenta; Per Ola Kristensson

doi:10.1145/2669485.2669511

User-defined interface gestures: dataset and analysis

Daniela Grijincu, Miguel Nacenta, Per Ola Kristensson

School of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	Proceedings of the 9th ACM International Conference on Interactive Tabletops and Surfaces (ITS 2014)
Place of Publication	New York, NY
Publisher	ACM
Pages	25-34
Number of pages	10
ISBN (Electronic)	9781450325875
DOIs	https://doi.org/10.1145/2669485.2669511
Publication status	Published - 16 Nov 2014

Keywords

Gesture design
User-defined gestures
Gesture elicitation
Gesture analysis methodology
Gesture annotation
Gesture memorability
Gestures
Gesture datasets
Crowdsourcing

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10.1145/2669485.2669511

GrijincuNacentaKristensson-UserDefinedInterfaceGesturesDataset
© 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
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Cite this

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title = "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.",

keywords = "Gesture design, User-defined gestures, Gesture elicitation, Gesture analysis methodology, Gesture annotation, Gesture memorability, Gestures, Gesture datasets, Crowdsourcing",

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N2 - 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.

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KW - User-defined gestures

KW - Gesture elicitation

KW - Gesture analysis methodology

KW - Gesture annotation

KW - Gesture memorability

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KW - Gesture datasets

KW - Crowdsourcing

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DO - 10.1145/2669485.2669511

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BT - Proceedings of the 9th ACM International Conference on Interactive Tabletops and Surfaces (ITS 2014)

PB - ACM

CY - New York, NY

ER -

User-defined interface gestures: dataset and analysis

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Keywords

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