Keywords

automated interviewing, credibility assessment, deception detection, facial expression recognition, facial rigidity analysis, risk assessment

Abstract

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.

Original Publication Citation

"A Video-Based Screening System for Automated Risk Assessment Using Nuanced Facial Features", Edition 3, Volume 35, Pages 994--994, Journal of Management Information Systems, 2018

Document Type

Peer-Reviewed Article

Publication Date

2017

Publisher

Journal of Management Information Systems

Language

English

College

Marriott School of Business

Department

Information Systems Management

University Standing at Time of Publication

Associate Professor

Download

Share

COinS