Eye Gaze Tracking for Detecting Non-verbal Communication in Meeting Environments
Open access
Date
2020Type
- Conference Paper
ETH Bibliography
yes
Altmetrics
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%. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000402355Publication status
publishedExternal links
Book title
Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and ApplicationsVolume
Pages / Article No.
Publisher
SciTePressEvent
Subject
Eye Gaze; Eye Tracker; OpenFace; Machine Learning; Support Vector Machine; Regression; Data ProcessingOrganisational unit
08844 - Kunz, Andreas (Tit.-Prof.) / Kunz, Andreas (Tit.-Prof.)
Funding
177542 - Barrierefreie Besprechungszimmer für sehbehinderte Menschen (SNF)
More
Show all metadata
ETH Bibliography
yes
Altmetrics