Title of the Talk: Face Morphing Attack Detection
Presenter: Christoph Busch
Abstract: Widespread deployment of Automatic Border Control (ABC), along with electronic Machine Readable Travel Documents (eMRTD) for traveler verification, has enabled a prominent use case of face biometrics in border control applications. The trust anchor are biometric passports. Many countries issue eMRTD passports on the basis of a printed biometric face photo submitted by the applicant, a procedure which allows the possibility of the photo being either altered to beautify the subject’s appearance or morphed to conceal his/her identity. If an eMRTD passport is issued with a morphed facial image, two or more data subjects can then use it to pass a border control. This talk will discuss the morphing attack problem and indicate early solutions to detect such morphed facial images.
Biography: Christoph Busch is a member of the Department of Information Security and Communication Technology (IIK) at the Norwegian University of Science and Technology (NTNU), Norway. He holds a joint appointment with the computer science faculty at Hochschule Darmstadt (HDA), Germany. Further he lectures the course Biometric Systems at Denmark’s DTU since 2007. On behalf of the German BSI he has been the coordinator for the project series BioIS, BioFace, BioFinger, BioKeyS Pilot-DB, KBEinweg and NFIQ 2.0. In the European research program he was initiator of the Integrated Project 3D-Face, FIDELITY and iMARS. Further he was/is partner in the projects TURBINE, BEST Network, ORIGINS, INGRESS, PIDaaS, SOTAMD, RESPECT and TReSPAsS. He is also principal investigator in the German National Research Center for Applied Cybersecurity (ATHENE). Moreover Christoph Busch is co-founder and member of board of the European Association for Biometrics (www.eab.org) that was established in 2011 and assembles in the meantime more than 200 institutional members. Christoph co-authored more than 500 technical papers and has been a speaker at international conferences. He is member of the editorial board of the IET journal on Biometrics and of IEEE TIFS journal. Furthermore he chairs the TeleTrusT biometrics working group as well as the German standardization body on Biometrics and is convenor of WG3 in ISO/IEC JTC1 SC37.
Title of the Talk: Perceiving Faces in 2D Images from 3D Perspective
Presenter: Qijun Zhao
Abstract:The face reveals a lot of information of humans, for example, identity, race, gender, age, emotion, intention, and health. 3D face models are thus widely studied in many disciplines. Yet, acquisition of 3D faces is still much more expensive and less convenient than acquisition of 2D face images, making it unaffordable to deploy 3D face technology in many real-world applications. Our research aims to reconstruct 3D face shapes from either single or multiple uncalibrated 2D face images to facilitate the perception of faces. This talk will introduce our recent progress along this direction. The methods we propose enable not only efficient generation of 3D face models when only 2D imaging devices are available, but also effective exploration of 3D face information for improving facial identity and expression recognition accuracy. We believe that 3D faces will play increasingly important roles in many applications with the rapid development of 3D face acquisition, modeling and processing methods.
Biography: Qijun Zhao is currently a professor in the College of Computer Science at Sichuan University. He obtained his B.Sc. and M.Sc. degrees in computer science both from Shanghai Jiao Tong University, and his Ph.D. degree in computer science from the Hong Kong Polytechnic University. He worked as a post-doc research fellow in the Pattern Recognition and Image Processing Lab at Michigan State University from 2010 to 2012, and as a visiting professor at Tibet University from 2019 to 2020. His recent research interests lie in 3D face modeling and recognition, with applications to forensics, intelligent video surveillance, mobile security, healthcare, and human-computer interactions. Dr. Zhao has published about 100 papers in academic conferences and journals, including CVPR, ECCV, AAAI, ICB, IEEE TPAMI, IEEE TIFS, and PR, and been granted for about 10 patents. He is the principal investigator for projects funded by NSFC, the National Key Research and Development Program of China, and many projects funded by companies. Dr. Zhao is a reviewer for many renowned field journals and conferences, such as IEEE TPAMI, IEEE TIFS, IJCV, PR, PRL, ICCV, CVPR, ECCV, and FG. He served as a program committee co-chair for the 11th Chinese Conference on Biometric Recognition (CCBR 2016), and the 2018 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA), and as a face recognition area co-chair for the 9th IEEE International Conference on Biometrics: Theory, Applications, and Systems (BTAS 2018), and the 2021 International Joint Conference on Biometrics (IJCB 2021).
Title of the Talk: Federated Learning-based Biometrics Authentication on Mobile Devices
Presenter: Vishal Patel
Abstract: Federated learning is a decentralized machine learning approach that enables multiple local devices to collaboratively learn a global model with the help of a server while preserving privacy of data at local devices. In this talk, I will first give an overview of federated learning and then present its application in biometrics-based active authentication. I will discuss merits and drawbacks of available approaches and identify promising avenues of research in this rapidly evolving field.
Biography: Vishal M. Patel [SM’15] is an Assistant Professor in the Department of Electrical and Computer Engineering (ECE) at Johns Hopkins University. Prior to joining Hopkins, he was an A. Walter Tyson Assistant Professor in the Department of ECE at Rutgers University and a member of the research faculty at the University of Maryland Institute for Advanced Computer Studies (UMIACS). He completed his Ph.D. in Electrical Engineering from the University of Maryland, College Park, MD, in 2010. His current research interests include signal processing, computer vision, and pattern recognition with applications in biometrics and imaging. He has received a number of awards including, the 2021 NSF CAREER Award, the 2016 ONR Young Investigator Award, the 2016 Jimmy Lin Award for Invention, A. Walter Tyson Assistant Professorship Award, Best Paper Award at IEEE AVSS 2017 & 2019, Best Paper Award at IEEE BTAS 2015, Honorable Mention Paper Award at IAPR ICB 2018, two Best Student Paper Awards at IAPR ICPR 2018, and Best Poster Awards at BTAS 2015 and 2016. He is an Associate Editor of the IEEE Signal Processing Magazine, Pattern Recognition Journal, and serves on the Machine Learning for Signal Processing (MLSP) Committee of the IEEE Signal Processing Society. He serves as the vice president of conferences for the IEEE Biometrics Council.