Abstract
In this study, we address a cross-domain problem of applying computer vision approaches to reason about human facial behaviour when people play The Resistance game. To capture the facial behaviours, we first collect several hours of video where the participants playing The Resistance game assume the roles of deceivers (spies) vs truth-tellers (villagers). We develop a novel attention-based neural network (NN) that advances the state of the art in understanding how a NN predicts the players' roles. This is accomplished by discovering through learning those pixels and related frames which are discriminative and contributed the most to the NN's inference. We demonstrate the effectiveness of our attention-based approach in discovering the frames and facial Action Units (AUs) that contributed to the NN's class decision. Our results are consistent with the current communication theory on deception.
Original language | English (US) |
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State | Published - 2020 |
Externally published | Yes |
Event | 30th British Machine Vision Conference, BMVC 2019 - Cardiff, United Kingdom Duration: Sep 9 2019 → Sep 12 2019 |
Conference
Conference | 30th British Machine Vision Conference, BMVC 2019 |
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Country/Territory | United Kingdom |
City | Cardiff |
Period | 9/9/19 → 9/12/19 |
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition