Border Security Credibility Assessments via Heterogeneous Sensor Fusion

Derrick, Douglas C.; Elkins, Aaron; Burgoon, Judee K.; Nunamaker, Jay F.; Zeng, Daniel

doi:10.1109/mis.2010.79

Cited by 36 publications

(14 citation statements)

References 15 publications

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“…For instance, when people were attempting deception, not only did the pitch (frequency) of the voice rise and become more varied, but also the periods during which the loudness of the voice did not change grew longer and more varied in length. The research also showed that the LDV was effective at detecting pulse and respiration rate, and that slower rates of inter-beat deceleration were associated with attempts to deceive (Derrick, et al 2010). However, normal movements of the subjects made it difficult to keep the LDV accurately trained on the part of the neck where data could be collected.…”

Section: [Figure 6 About Here]mentioning

confidence: 89%

“…Proof-of-concept research focused on assessing the technical feasibility of real-time credibility assessment for a) kinesic cues, such as gestures, micro-movements, eye-gaze, and body rigidity; vocalic cues such as speech duration, time-to-response when a question was asked, and latency; voice pitch and amplitude; and physiological cues: blood pressure, heart and respiration rate, facial skin temperature, and facial pore size (Derrick, et al 2010). Early research showed that certain vocalic cues reliably correlated strongly with intent to deceive.…”

Section: [Figure 6 About Here]mentioning

confidence: 99%

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The Last Research Mile: Achieving Both Rigor and Relevance in Information Systems Research

Nunamaker

Briggs

Derrick

et al. 2015

Journal of Management Information Systems

Self Cite

122

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From our desk chairs it may be tempting to work up an idea, build a quick prototype, test it in a lab, and say, "Our work here is done; the rest is merely details." More scholarly knowledge awaits discovery, however, by researchers who shepherd an information systems (IS) solution through the last research mile, that is, through successful transition to the workplace. Going the last research mile means using scientific knowledge and methods to address important unsolved classes of problems for real people with real stakes in the outcomes. The last research mile proceeds in three stages: proof-of-concept research to demonstrate the functional feasibility of a solution; proof-of-value research to investigate whether a solution can create value across a variety of conditions; and proof-of-use research to address complex issues of operational feasibility. The last research mile ends only when practitioners routinely use a solution in the field. We argue that going the last research mile negates the assumption that one must trade off rigor and relevance, showing it to be it a false dilemma. Systems researchers who take their solutions through the last research mile may ultimately have the greatest impact on science and society. We demonstrate the last research mile with cases from our own work and the work of others spanning more than forty years. As a professor of information systems at San Diego State University, Robert O. Briggs researches the cognitive foundations of collaboration and uses his findings to design new collaborative work practices and technologies. He is cofounder of the collaboration engineering field and co-inventor of the ThinkLets design pattern language for collaborative work processes. He has made exploratory, theoretical, experimental, and technological contributions to the areas of team productivity, technology-supported learning, ideation, creativity, consensus, satisfaction, willingness to change, and technology transition. He has designed collaboration systems and collaborative workspaces for industry, academia, government, and the military. He co-chairs the Collaboration Systems and Technology track for the Hawaii International Conference on System Sciences. He lectures worldwide on collaboration theory and practice, and on the logic of scientific inquiry. He has published more than two hundred scholarly works collaboration systems and technology, addressing issues team productivity, technology-supported learning, creativity, satisfaction, and technology transition. He earned his doctorate Management Information Systems at the University of Arizona in 1994. Air Force officer. He has extensive experience working with the Department of Defense. As a contractor and academic, he has been awarded contracts and grants totaling $39.85 Million over the last 12 years (principle investigator awards total $16.89 Million). Doug has published 41 peer-reviewed journal articles and conference proceedings. Douglas C Derrick Gerhard SchwabeGerhard Schwabe is a full professor of at the Universit...

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Section: [Figure 6 About Here]mentioning

confidence: 89%

Section: [Figure 6 About Here]mentioning

confidence: 99%

The Last Research Mile: Achieving Both Rigor and Relevance in Information Systems Research

Nunamaker

Briggs

Derrick

et al. 2015

Journal of Management Information Systems

Self Cite

122

View full text Add to dashboard Cite

show abstract

“…Derrick et al conducted a study on deception detection using a mock crime experimental paradigm that included the fusion of multiple behavioral sensors (Derrick, Elkins, Burgoon, Nunamaker Jr, & Zeng, 2010). Derrick et al found that deceivers increased their heart rate (measured using LDV) in anticipation to lie relevant stimulus and then decreased their heart rate after experiencing the stimulus.…”

Section: Fusionmentioning

confidence: 99%

Unobtrusive Deception Detection

Elkins

Zafeiriou

Pantić

et al. 2015

The Oxford Handbook of Affective Computing

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“…The most significant achievement is an extension of access systems [3] to the large-scale A-machines, for applications such as mass public events and automated border crossing [6], [14], [7]. Various techniques have been developed in the last decade, based on multi-modal behavior biometrics [1], [4], [6], [14]. For example, in an AVATAR machine, vocal pitch frequency of voice, quality body movement, eye movement, pupil dilation in visual and infrared band, and facial expressions, are collected and analyzed [2] (Fig.…”

Section: Brief Overview Of the Evolving Concept Of A-machinesmentioning

confidence: 99%

Biometric Intelligence in Authentication Machines: from Talking Faces to Talking Robots

Eastwood

Shmerko

Yanushkevich

et al. 2014

2014 IIAI 3rd International Conference on Advanced Applied Informatics

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Biometric-based intelligence in authentication machines (A-machines) concerns with the problem of balancing human and machine functions in applications such as mass public events and border crossing. The focus of this paper is intelligent human-machine interfacing of behavior biometrics, which seems to play an important role in future generations of A-machines. Various pilot projects use the "talking face" technology. We suggest further improvement to A-machines based on "talking robot" technology: while interviewing the traveler, a humanoid robot recognizes faces and expressions, verifies the e-passports and the traveler (using his/her biometrics), connects with a watchlist (database), generates cognitive questions and analyzes answers, as well as detects soft biometric features in visual and infrared spectrum bands, such as temperature and blood pressure. Various parts of such technology have been implemented, and the feasibility of assembling such a multifunctional system in the form of a robot is to be studied and understood. This paper presents a survey of the related work, and also provides the authors' vision of future generations of A-machines and their applications.

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Border Security Credibility Assessments via Heterogeneous Sensor Fusion

Cited by 36 publications

References 15 publications

The Last Research Mile: Achieving Both Rigor and Relevance in Information Systems Research

The Last Research Mile: Achieving Both Rigor and Relevance in Information Systems Research

Unobtrusive Deception Detection

Biometric Intelligence in Authentication Machines: from Talking Faces to Talking Robots

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