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Proceedings Paper

An automated process for deceit detection
Author(s): Ifeoma Nwogu; Mark Frank; Venu Govindaraju
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Paper Abstract

In this paper we present a prototype for an automated deception detection system. Similar to polygraph examinations, we attempt to take advantage of the theory that false answers will produce distinctive measurements in certain physiological manifestations. We investigate the role of dynamic eye-based features such as eye closure/blinking and lateral movements of the iris in detecting deceit. The features are recorded both when the test subjects are having non-threatening conversations as well as when they are being interrogated about a crime they might have committed. The rates of the behavioral changes are blindly clustered into two groups. Examining the clusters and their characteristics, we observe that the dynamic features selected for deception detection show promising results with an overall deceptive/non-deceptive prediction rate of 71.43% from a study consisting of 28 subjects.

Paper Details

Date Published: 14 April 2010
PDF: 10 pages
Proc. SPIE 7667, Biometric Technology for Human Identification VII, 76670R (14 April 2010); doi: 10.1117/12.851407
Show Author Affiliations
Ifeoma Nwogu, Univ. at Buffalo (United States)
Mark Frank, Univ. at Buffalo (United States)
Venu Govindaraju, Univ. at Buffalo (United States)

Published in SPIE Proceedings Vol. 7667:
Biometric Technology for Human Identification VII
B. V. K. Vijaya Kumar; Salil Prabhakar; Arun A. Ross, Editor(s)

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