Causal Inference in Nonverbal Dyadic Communication with Relevant Interval Selection and Granger Causality

Lea Müller, Maha Shadaydeh, Martin Thümmel, Thomas Kessler, Dana Schneider, Joachim Denzler

2019

Abstract

Human nonverbal emotional communication in dyadic dialogs is a process of mutual influence and adaptation. Identifying the direction of influence, or cause-effect relation between participants, is a challenging task due to two main obstacles. First, distinct emotions might not be clearly visible. Second, participants cause-effect relation is transient and variant over time. In this paper, we address these difficulties by using facial expressions that can be present even when strong distinct facial emotions are not visible. We also propose to apply a relevant interval selection approach prior to causal inference to identify those transient intervals where adaptation process occurs. To identify the direction of influence, we apply the concept of Granger causality to the time series of facial expressions on the set of relevant intervals. We tested our approach on synthetic data and then applied it to newly, experimentally obtained data. Here, we were able to show that a more sensitive facial expression detection algorithm and a relevant interval detection approach is most promising to reveal the cause-effect pattern for dyadic communication in various instructed interaction conditions.

Paper Citation

in Harvard Style

Müller L., Shadaydeh M., Thümmel M., Kessler T., Schneider D. and Denzler J. (2019). Causal Inference in Nonverbal Dyadic Communication with Relevant Interval Selection and Granger Causality. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP; ISBN 978-989-758-354-4, SciTePress, pages 490-497. DOI: 10.5220/0007399304900497

in Bibtex Style

@conference{visapp19,
author={Lea Müller and Maha Shadaydeh and Martin Thümmel and Thomas Kessler and Dana Schneider and Joachim Denzler},
title={Causal Inference in Nonverbal Dyadic Communication with Relevant Interval Selection and Granger Causality},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP},
year={2019},
pages={490-497},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007399304900497},
isbn={978-989-758-354-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP
TI - Causal Inference in Nonverbal Dyadic Communication with Relevant Interval Selection and Granger Causality
SN - 978-989-758-354-4
AU - Müller L.
AU - Shadaydeh M.
AU - Thümmel M.
AU - Kessler T.
AU - Schneider D.
AU - Denzler J.
PY - 2019
SP - 490
EP - 497
DO - 10.5220/0007399304900497
PB - SciTePress