Eye Gaze Tracking for Detecting Non-verbal Communication in Meeting Environments
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Author / Producer
Date
2020
Publication Type
Conference Paper
ETH Bibliography
yes
Citations
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Data
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 x 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%.
Permanent link
Publication status
published
External links
Book title
Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
Journal / series
Volume
2
Pages / Article No.
239 - 246
Publisher
SciTePress
Event
15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) / 4th International Conference on Human Computer Interaction Theory and Applications (HUCAPP 2020)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Eye Gaze; Eye Tracker; OpenFace; Machine Learning; Support Vector Machine; Regression; Data Processing
Organisational unit
08844 - Kunz, Andreas (Tit.-Prof.) / Kunz, Andreas (Tit.-Prof.)
Notes
Funding
177542 - Barrierefreie Besprechungszimmer für sehbehinderte Menschen (SNF)