TY - JOUR
T1 - A Video-Based Screening System for Automated Risk Assessment Using Nuanced Facial Features
AU - Pentland, Steven J.
AU - Twyman, Nathan W.
AU - Burgoon, Judee K.
AU - Nunamaker, Jay F.
AU - Diller, Christopher B.R.
N1 - Funding Information:
STEVEN J. PENTLAND ([email protected]; corresponding author) is a Ph.D. student at the University of Arizona. His research interests include interpersonal deception, affective computing, and automated interviewing. His work focuses on the extraction and analysis of nonverbal behaviors using remote sensing technology. He has contributed to a variety of projects supported by the National Science Foundation, Department of Homeland Security, and the Department of Defense.
Funding Information:
JUDEE K. BURGOON ([email protected]) is professor of communication, family studies and human development. She is the director of research for the Center for the Management of Information and site director for the National Science Foundation– sponsored Center for Identification Technology Research at the University of Arizona. She holds a doctorate in communication and educational psychology from West Virginia University. She has authored or edited 14 books and monographs and over 300 articles, chapters, and reviews related to nonverbal and relational communication, deception, the impact of new communication technologies on human–human and human–computer interaction, research methods, and public opinion toward the media. Her research has been supported by the National Science Foundation, the Department of Defense, the Department of Homeland Security, the National Center for Credibility Assessment, the National Institutes of Mental Health, and others.
Funding Information:
Acknowledgments: The Department of Homeland Security’s (DHS) National Center for Border Security and Immigration (BORDERS), the National Center for Credibility Assessment (NCCA), and the Center for Identification Technology Research (CITeR), a National Science Foundation (NSF) Industry/University Cooperative Research Center (I/ UCRC), provided funding for this research. Statements provided herein do not necessarily represent the opinions of the funding organizations.
Funding Information:
NATHAN W. TWYMAN ([email protected]) is an assistant professor of business and information technology at the Missouri University of Science and Technology. He received his Ph.D. in management information systems (IS) from the University of Arizona. His interests span the research on human–computer interaction, decision support systems and group support systems, virtual communities, credibility assessment systems, and health IS. He has been a principal investigator of and key contributor to research grants from the National Science Foundation, the Department of Homeland Security, and the Department of Defense. His industry experience is in data management, business intelligence, strategic planning, training, and electronics. His research is published in Journal of Management Information Systems, Journal of the AIS, and Information and Management.
Publisher Copyright:
Copyright © Taylor & Francis Group, LLC.
PY - 2017/10/2
Y1 - 2017/10/2
N2 - This study investigates the development of an automated interviewing system that uses facial behavior as an indicator of the risk of given illicit behavior. Traditional facial emotion indicators of risk in semistructured dialogue may have limitations in an automated approach. However, an initial analysis of mock crime interviews suggests that the face may exhibit some form of rigidity during highly structured interviews. An interviewing system design using facial rigidity analysis was implemented and experimentally evaluated, the results of which further reveal that the rigidity is fairly generalized across the face. Whereas existing theory traditionally focuses on leakage of facial expressions, this study provides evidence that neutralization of facial expression may be a valuable alternative for automated interviewing systems. The proof-of-concept system in this study may help human risk assessment move beyond traditional boundaries, into fields such as auditing, emergency room management, and security screening.
AB - This study investigates the development of an automated interviewing system that uses facial behavior as an indicator of the risk of given illicit behavior. Traditional facial emotion indicators of risk in semistructured dialogue may have limitations in an automated approach. However, an initial analysis of mock crime interviews suggests that the face may exhibit some form of rigidity during highly structured interviews. An interviewing system design using facial rigidity analysis was implemented and experimentally evaluated, the results of which further reveal that the rigidity is fairly generalized across the face. Whereas existing theory traditionally focuses on leakage of facial expressions, this study provides evidence that neutralization of facial expression may be a valuable alternative for automated interviewing systems. The proof-of-concept system in this study may help human risk assessment move beyond traditional boundaries, into fields such as auditing, emergency room management, and security screening.
UR - http://www.scopus.com/inward/record.url?scp=85039905632&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85039905632&partnerID=8YFLogxK
U2 - 10.1080/07421222.2017.1393304
DO - 10.1080/07421222.2017.1393304
M3 - Article
AN - SCOPUS:85039905632
SN - 0742-1222
VL - 34
SP - 970
EP - 993
JO - Journal of Management Information Systems
JF - Journal of Management Information Systems
IS - 4
ER -