How Video Meetings Change Your Expression

Sumit Sarin, Purva Tendulkar, Utkarsh Mall, Carl Vondrick

Abstract:

Do our facial expressions change when we speak over video
calls? Given two unpaired sets of videos of people, we seek to automatically find spatio-temporal patterns that are distinctive of each set.
Existing methods use discriminative approaches and perform post-hoc
explainability analysis. Such methods are insufficient as they are unable to provide insights beyond obvious dataset biases, and the explanations are useful only if humans themselves are good at the task. Instead,
we tackle the problem through the lens of generative domain translation: our method generates a detailed report of learned, input-dependent
spatio-temporal features and the extent to which they vary between the
domains. We demonstrate that our method can discover behavioral differences between conversing face-to-face (F2F) and on video-calls (VCs).
We also show the applicability of our method on discovering differences
in presidential communication styles. Additionally, we are able to predict temporal change-points in videos that decouple expressions in an
unsupervised way, and increase the interpretability and usefulness of our
model. Finally, our method, being generative, can be used to transform
a video call to appear as if it were recorded in a F2F setting. Experiments and visualizations show our approach is able to discover a range
of behaviors, taking a step towards deeper understanding of human behaviors.