@article{76b855e57f8643b6b1289dad21ce427d,
title = "Deception detection through automatic, unobtrusive analysis of nonverbal behavior",
abstract = "An approach for deception detection through automatic, unobtrusive analysis of nonverbal behavior was described. An automated unobtrusive system identifies behavioral patterns that indicate deception from nonverbal behavioral cues and classifies deception and truth more accurately than many humans. Automated systems can draw upon a wide variety of potential behavioral indicators of deception. It is expected that the automated systems might become reliable enough to replace humans in certain circumstances, thus allowing a redistribution of human assets.",
author = "Meservy, {Thomas O.} and Jensen, {Matthew L.} and John Kruse and Burgoon, {Judee K.} and Nunamaker, {Jay F.} and Twitchell, {Douglas P.} and Gabriel Tsechpenakis and Metaxas, {Dimitris N.}",
note = "Funding Information: Portions of this research were supported by funding from the US Air Force Office of Scientific Research under the US Department of Defense University Research Initiative (Grant #F49620-01-1-0394) and by the US Department of Homeland Security (Cooperative Agreement N66001-01-X-6042). This article{\textquoteright}s views, opinions, and findings are those of the authors and shouldn{\textquoteright}t be construed as official Department of Defense or Department of Homeland Security positions, policies, or decisions.",
year = "2005",
month = sep,
doi = "10.1109/MIS.2005.85",
language = "English (US)",
volume = "20",
pages = "36--43",
journal = "IEEE Intelligent Systems",
issn = "1541-1672",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "5",
}