Anticipating Averted Gaze in Dyadic Interactions
Philipp Müller, Ekta Sood, Andreas Bulling
Proc. ACM International Symposium on Eye Tracking Research and Applications (ETRA), pp. 1-10, 2020.
Overview of our eye contact anticipation method. Left: In the feature encoding network, each feature modality is fed through a fully connected layer (FC Layer) separately and the resulting representations are concatenated. Right: features are extracted on a feature window wf and fed through an embedding network consisting of a fully connected layer for each timestep separately, before they are fed to a LSTM network. At the last timestep of the feature window the LSTM outputs a classification score which is compared to ground truth extracted from the target window wt .Abstract
We present the first method to anticipate averted gaze in natural dyadic interactions. The task of anticipating averted gaze, i.e. that a person will not make eye contact in the near future, remains unsolved despite its importance for human social encounters as well as a number of applications, including human-robot interaction or conversational agents. Our multimodal method is based on a long short-term memory (LSTM) network that analyses non-verbal facial cues and speaking behaviour. We empirically evaluate our method for different future time horizons on a novel dataset of 121 YouTube videos of dyadic video conferences (74 hours in total). We investigate person-specific and person-independent performance and demonstrate that our method clearly outperforms baselines in both settings. As such, our work sheds light on the tight interplay between eye contact and other non-verbal signals and underlines the potential of computational modelling and anticipation of averted gaze for interactive applications.
Links
Paper: mueller20_etra.pdf
BibTeX
@inproceedings{mueller20_etra,
title = {Anticipating Averted Gaze in Dyadic Interactions},
author = {Philipp Müller and Ekta Sood and Andreas Bulling},
year = {2020},
booktitle = {Proc. ACM International Symposium on Eye Tracking Research and Applications (ETRA)},
pages = {1-10},
doi = {10.1145/3379155.3391332},
}