MUVTIME: A Multivariate Time Series Visualizer for Behavioral Science

Emanuel Sousa, Tiago Malheiro, Estela Bicho, Wolfram Erlhagen, Jorge Santos, Alfredo Pereira

Abstract

As behavioral science becomes progressively more data driven, the need is increasing for appropriate tools for visual exploration and analysis of large datasets, often formed by multivariate time series. This paper describes MUVTIME, a multimodal time series visualization tool, developed in Matlab that allows a user to load a time series collection (a multivariate time series dataset) and an associated video. The user can plot several time series on MUVTIME and use one of them to do brushing on the displayed data, i.e. select a time range dynamically and have it updated on the display. The tool also features a categorical visualization of two binary time series that works as a high-level descriptor of the coordination between two interacting partners. The paper reports the successful use of MUVTIME under the scope of project TURNTAKE, which was intended to contribute to the improvement of human-robot interaction systems by studying turn-taking dynamics (role interchange) in parent-child dyads during joint action.

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Paper Citation


in Harvard Style

Sousa E., Malheiro T., Bicho E., Erlhagen W., Santos J. and Pereira A. (2016). MUVTIME: A Multivariate Time Series Visualizer for Behavioral Science . In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: IVAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 165-176. DOI: 10.5220/0005725301650176


in Bibtex Style

@conference{ivapp16,
author={Emanuel Sousa and Tiago Malheiro and Estela Bicho and Wolfram Erlhagen and Jorge Santos and Alfredo Pereira},
title={MUVTIME: A Multivariate Time Series Visualizer for Behavioral Science},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: IVAPP, (VISIGRAPP 2016)},
year={2016},
pages={165-176},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005725301650176},
isbn={978-989-758-175-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: IVAPP, (VISIGRAPP 2016)
TI - MUVTIME: A Multivariate Time Series Visualizer for Behavioral Science
SN - 978-989-758-175-5
AU - Sousa E.
AU - Malheiro T.
AU - Bicho E.
AU - Erlhagen W.
AU - Santos J.
AU - Pereira A.
PY - 2016
SP - 165
EP - 176
DO - 10.5220/0005725301650176