Dyadic Synchrony as a Measure of Trust and Veracity



We investigate how degree of interactional synchrony can signal whether trust is present, absent, increasing or declining. We propose an automated, data-driven and unobtrusive framework for deception detection and analysis in interrogation interviews from visual cues only. Our framework consists of the face tracking, the gesture detection, the expression recognition, and the synchrony estimation. This framework is able to automatically track gestures and expressions of both the subject and the interviewer, extract normalized meaningful synchrony features and learn classification models for deception recognition. To validate these proposed synchrony features, extensive experiments have been conducted on a database of $242$ video samples, and shown that these features are very effective at detecting deceptions.


  • X. Yu, S. Zhang, Z. Yan, F. Yang, J. Huang, N.E. Dunbar, M.L. Jensen, J.K. Burgoon and D.N. Metaxas, "Is Interactional Dissynchrony a Clue to Deception? Insights from Automated Analysis of Nonverbal Visual Cues", IEEE Transactions on Cybernetics, 2014.