Eye Gaze Tracking for Detecting Non-verbal Communication in Meeting Environments

Naina Dhingra, Christian Hirt, Manuel Angst, Andreas Kunz

Abstract

Non-verbal communication in a team meeting is important to understand the essence of the conversation. Among other gestures, eye gaze shows the focus of interest on a common workspace and can also be used for an interpersonal synchronisation. If this non-verbal information is missing and or cannot be perceived by blind and visually impaired people (BVIP), they would lack important information to get fully immersed in the meeting and may feel alienated in the course of the discussion. Thus, this paper proposes an automatic system to track where a sighted person is gazing at. We use the open source software ’OpenFace’ and develop it as an eye tracker by using a support vector regressor to make it work similarly to commercially available expensive eye trackers. We calibrate OpenFace using a desktop screen with a 2×3 box matrix and conduct a user study with 28 users on a big screen (161.7 cm x 99.8 cm x 11.5 cm) with a 1×5 box matrix. In this user study, we compare the results of our developed algorithm for OpenFace to an SMI RED 250 eye tracker. The results showed that our work achieved an overall relative accuracy of 58.54%.

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Paper Citation


in Harvard Style

Dhingra N., Hirt C., Angst M. and Kunz A. (2020). Eye Gaze Tracking for Detecting Non-verbal Communication in Meeting Environments.In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: HUCAPP, ISBN 978-989-758-402-2, pages 239-246. DOI: 10.5220/0009359002390246


in Bibtex Style

@conference{hucapp20,
author={Naina Dhingra and Christian Hirt and Manuel Angst and Andreas Kunz},
title={Eye Gaze Tracking for Detecting Non-verbal Communication in Meeting Environments},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: HUCAPP,},
year={2020},
pages={239-246},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009359002390246},
isbn={978-989-758-402-2},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: HUCAPP,
TI - Eye Gaze Tracking for Detecting Non-verbal Communication in Meeting Environments
SN - 978-989-758-402-2
AU - Dhingra N.
AU - Hirt C.
AU - Angst M.
AU - Kunz A.
PY - 2020
SP - 239
EP - 246
DO - 10.5220/0009359002390246