Content uploaded by Dmitry O. Gorodnichy
Author content
All content in this area was uploaded by Dmitry O. Gorodnichy on Feb 27, 2020
Content may be subject to copyright.
A preview of the PDF is not available
Biometric-enabled Interview-Assisting Traveller Screening technology for Automated Border Control
Abstract and Figures
This report presents the deliverables for the "Roadmap for Biometrics at the Border" (CSSP-2015-TI-2158) study conducted by the Canada Border Services Agency (CBSA) in partnership with University of Arizona (UA) and San Diego State University (SDSU) through support from the Defence Research and Development Canada, Canadian Safety and Security Program (CSSP). The main objective of this study was to generate critical knowledge related to the use of biometric-enabled Interview Assisting Traveller Screening (IATS) technology, such as AVATAR kiosks developed by UA and SDSU. The deliverables include: overview of manual behaviour screening limitations, overview of challenges related to designing biometric-enabled behaviour screening (BEBS) systems, development of a novel framework for designing and evaluating BEBS systems, conducting a mock-up experiment with the AVATAR kiosk at the CBSA, and finally, recommendations based on the lessons and insights learnt from the conducted evaluations.
The publication of this article is enabled by the Scientific Integrity Policy released by the Canada Border Agency Services (CBSA) in December 2019 and is done in support of the Government of Canada's National Action Plan on Open Government and Open Science.
This article is the unabridged version of the report that was prepared by the authors for the CSSP-2015-TI-2158 Study. The reference to the abridged published version is provided below:
Dmitry O. Gorodnichy, “Design and Evaluation of Biometric-enabled Interview-Assisting Traveller Screening technology for Automated Border Control. CSSP-2015-TI-2158 Study . Final Report", Technical Report, DRDC-RDDC-2018-C223, Online: http://cradpdf.drdc-rddc.gc.ca/PDFS/unc331/p808530_A1b.pdf.
Figures - uploaded by Dmitry O. Gorodnichy
Author content
All figure content in this area was uploaded by Dmitry O. Gorodnichy
Content may be subject to copyright.
ResearchGate has not been able to resolve any citations for this publication.
This report presents the list of the new and revised biometric terms recommended for automated border control and video surveillance applications. These terms have been developed by the CBSA Science and Engineering Directorate as a result of its work on the “PROVE-IT(FRiV)”, “PROVE-IT(VA)” and “ART in ABC" studies, which were conducted by the directorate in partnership with academic and government partners under funding from Defence Research and Development Canada, with additional input from ISO SC 37 SMC1 members.
This report presents a survey of evaluation datasets, metrics and practices used by the scienti�c
community pertaining to the evaluation of video analytics in the video surveillance context.
The focus of the survey is on the task of visually tracking people in video, and its application to
loitering and tailgating detection. The related key results from the TRECVID video analytic
evaluation conducted by the National Institute of Standards and Technology (NIST) are
presented.
How should ecologists and evolutionary biologists analyze nonnormal data that involve random effects? Nonnormal data such as counts or proportions often defy classical statistical procedures. Generalized linear mixed models (GLMMs) provide a more flexible approach for analyzing nonnormal data when random effects are present. The explosion of research on GLMMs in the last decade has generated considerable uncertainty for practitioners in ecology and evolution. Despite the availability of accurate techniques for estimating GLMM parameters in simple cases, complex GLMMs are challenging to fit and statistical inference such as hypothesis testing remains difficult. We review the use (and misuse) of GLMMs in ecology and evolution, discuss estimation and inference and summarize 'best-practice' data analysis procedures for scientists facing this challenge.
We have created an automated kiosk that uses embodied intelligent agents to interview individuals and detect changes in arousal, behavior, and cognitive effort by using psychophysiological information systems. In this paper, we describe the system and propose a unique class of intelligent agents, which are described as Special Purpose Embodied Conversational Intelligence with Environmental Sensors (SPECIES). SPECIES agents use heterogeneous sensors to detect human physiology and behavior during interactions, and they affect their environment by influencing human behavior using various embodied states (i. e., gender and demeanor), messages, and recommendations. Based on the SPECIES paradigm, we present three studies that evaluate different portions of the model, and these studies are used as foundational research for the development of the automated kiosk. The first study evaluates human-computer interaction and how SPECIES agents can change perceptions of information systems by varying appearance and demeanor. Instantiations that had the agents embodied as males were perceived as more powerful, while female embodied agents were perceived as more likable. Similarly, smiling agents were perceived as more likable than neutral demeanor agents. The second study demonstrated that a single sensor measuring vocal pitch provides SPECIES with environmental awareness of human stress and deception. The final study ties the first two studies together and demonstrates an avatar-based kiosk that asks questions and measures the responses using vocalic measurements.
Directly connected to the brain, the eyes are the last part of our body we lose control of. For some persons, such as those suffered from a brain-stem stroke, the eyes provide the only means of communication with the world. The eye blinks for such persons are used to make their lexicon and the goal of many rehabilitation centers worldwide is to build tools that would allow automatic detection of the eye blink based lexicon. The tools designed so far are very cumbersome and still do not show the desired performance. At the same time, recent advances in computer hardware and computer vision, in particular, in motion and change detection, offered practitioners a new way for detecting blinks based on video observations of the person's face. This paper overviews different techniques to the problem and describes a vision-based system which is presently being tested in one of the rehabilitation centres. We show how to reliably detect a two-eye blink with a help of an off-the-shelf web-camera and present an approach to the detection a single-eye blink (wink) - this type of blinks is much harder to detect due the lack of spacial constrains, it is however the only type of movement some patients can exhibit.
This paper provides an introduction to mixed-effects models for the analysis of repeated measurement data with subjects and items as crossed random effects. A worked-out example of how to use recent software for mixed-effects modeling is provided. Simulation studies illustrate the advantages offered by mixed-effects analyses compared to traditional analyses based on quasi-F tests, by-subjects analyses, combined by-subjects and by-items analyses, and random regression. Applications and possibilities across a range of domains of inquiry are discussed.
Face Recognition and Event Detection in Video: An Overview of PROVE-IT Projects
- D Bissessar
- E Choy
- D Gorodnichy
- T Mungham
D. Bissessar, E. Choy, D. Gorodnichy, T. Mungham, "Face Recognition and Event Detection in Video: An Overview of PROVE-IT
Projects", Technical Report DRDC-RDDC-2014-C167, http://cradpdf.drdc-rddc.gc.ca/PDFS/unc157/p800402_A1b.pdf
CBET evaluation of voice biometrics
- O Dmitry
- Michael Gorodnichy
- Dave Thieme
- Jessica Bissessar
- Elan Chung
- Jonathon Dubrofsky
- Lee
Dmitry O. Gorodnichy, Michael Thieme, Dave Bissessar, Jessica Chung, Elan Dubrofsky, Jonathon Lee, "CBET evaluation of voice
biometrics. In Proc. SPIE Defence, Security & Sensing Conference, 2011. https://www.researchgate.net/publication/228408767_C-BET_evaluation_of_voice_biometrics
Biological Models of Vision and Attention for Face Detection in Natural Scenes. Surprise Approach
- Laurent Itti
Laurent Itti,"Biological Models of Vision and Attention for Face Detection in Natural Scenes. Surprise Approach", IEEE Workshop on
Face Processing in Video, June 28, 2004, Washington, D.C., USA www.visioninterface.net/fpiv04/papers.html