NDLI: Is Interactional Dissynchrony a Clue to Deception? Insights From Automated Analysis of Nonverbal Visual Cues

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Issue 2

Issue 1

Year : 2014 Volume : 44

Year : 2013 Volume : 43

Is Interactional Dissynchrony a Clue to Deception? Insights From Automated Analysis of Nonverbal Visual Cues

Content Provider	IEEE Xplore Digital Library
Author	Xiang Yu Shaoting Zhang Zhennan Yan Fei Yang Junzhou Huang Dunbar, N.E. Jensen, M.L. Burgoon, J.K. Metaxas, D.N.
Copyright Year	2013
Abstract	Detecting deception in interpersonal dialog is challenging since deceivers take advantage of the give-and-take of interaction to adapt to any sign of skepticism in an interlocutor's verbal and nonverbal feedback. Human detection accuracy is poor, often with no better than chance performance. In this investigation, we consider whether automated methods can produce better results and if emphasizing the possible disruption in interactional synchrony can signal whether an interactant is truthful or deceptive. We propose a data-driven and unobtrusive framework using visual cues that consists of face tracking, head movement detection, facial expression recognition, and interactional synchrony estimation. Analysis were conducted on 242 video samples from an experiment in which deceivers and truth-tellers interacted with professional interviewers either face-to-face or through computer mediation. Results revealed that the framework is able to automatically track head movements and expressions of both interlocutors to extract normalized meaningful synchrony features and to learn classification models for deception recognition. Further experiments show that these features reliably capture interactional synchrony and efficiently discriminate deception from truth.
Page Count	15
File Size	2477981
Starting Page	492
Ending Page	506
File Format	PDF
ISSN	21682267
Volume Number	45
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Face Shape Tracking Face recognition Educational institutions interactional synchrony Deception detection expression recognition face tracking gesture detection
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Information Systems Electrical and Electronic Engineering Human-Computer Interaction Computer Science Applications Software

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