Face Recognition Performance Workshop
20 July, 13:00-17:00
The workshop will cover the latest updates in face recognition performance including results from the four ongoing tracks of the new NIST Face Recognition Vendor Test (FRVT). The session will give introductory material on biometrics performance comparing metrics for matching vs transactional rates, identification vs verification, false positives vs negatives. Thereafter more detail on the following topics will be covered include: gains from the new generation of algorithms; description and quantification of demographic effects; statements on ageing; scalability of accuracy and speed in large populations.
The workshop will include information on how face recognition fails, and will contrast face with other modalities. Additionally, the session will cover face image quality assessment, face-aware capture systems, recent work on consensus standards, in particular giving an update to the ISO/IEC 19795 testing and reporting standards and the ISO/IEC 30107 presentation attack detection standards, and future activities under FRVT.
Who should attend: end-users, integrators, application developers and others interested in the technical performance aspects of face detection and recognition.
Patrick Grother is a scientist at the National Institute of Standards in Technology (NIST) responsible for biometric standards and testing. He leads the IREX, FRVT and FIVE evaluations of iris and face recognition technologies that support biometrics in national scale identity management. He co-chairs NIST’s International Face Performance Conference on measurement, metrics and certification. Patrick edits the biometrics specifications for the US Government’s PIV credentialing program, for which he received his second Department of Commerce Gold Medal. Patrick assists a number of US Government agencies on research, development and evaluation. He serves as chair of the SC37 committee on Biometrics and is editor of five ISO standards there. He received the IEC 1906 Award in 2009 and the ANSI Lohse IT Medal in 2013.
Mei Ngan is a scientist at the National Institute of Standards and Technology (NIST). Mei received the B.S. degree in computer engineering from the University of Maryland, College Park in 2003 and the M.S. in computer science from the Johns Hopkins University in 2006. Her research focus includes evaluation of tattoo recognition and face recognition technologies. Mei has authored and co-authored several technical publications, including outcomes from large-scale evaluation of one-to-many face identification algorithms, performance of facial age and gender estimation algorithms, and publication of a seminal open tattoo database for developing tattoo recognition research, which she received the Special Contribution Award for at the 2015 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA).
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