CCBR 2017 深圳






David Zhang

Chair Professor, Hong Kong Polytechnic University

Fellow of IEEE and IAPR

     Biography:David Zhang graduated in Computer Science from Peking University. He received his MSc in 1982 and his PhD in 1985 in both Computer Science from the Harbin Institute of Technology (HIT), respectively. From 1986 to 1988 he was a Postdoctoral Fellow at Tsinghua University and then an Associate Professor at the Academia Sinica, Beijing. In 1994 he received his second PhD in Electrical and Computer Engineering from the University of Waterloo, Ontario, Canada. Currently, he is a Chair Professor at the Hong Kong Polytechnic University where he is the Founding Director of Biometrics Research Centre (UGC/CRC) supported by the Hong Kong SAR Government in 1998. He also serves as Visiting Chair Professor in Tsinghua University and HIT, and Adjunct Professor in Shanghai Jiao Tong University, Peking University, National University of Defense Technology and the University of Waterloo. He is the Founder and Editor-in-Chief, International Journal of Image and Graphics (IJIG); Book Editor, Springer International Series on Biometrics (KISB); Organizer, the first International Conference on Biometrics Authentication (ICBA); Associate Editor of more than ten international journals including IEEE Transactions and so on. So far, he has published over 20 monographs, 400 international journal papers and 40 patents from USA/Japan/HK/China. He has been continuously listed as a Highly Cited Researchers in Engineering by Clarivate Analytics (formerly known as Thomson Reuters) in 2014, 2015, 2016 and 2017, respectively. Professor Zhang is a Croucher Senior Research Fellow, Distinguished Speaker of the IEEE Computer Society, and a Fellow of both IEEE and IAPR.
     Title:Advanced Biometrics
   Abstract:In recent times, an increasing, worldwide effort has been devoted to the development of automatic personal identification systems that can be effective in a wide variety of security contexts. As one of the most powerful and reliable means of personal authentication, biometrics has been an area of particular interest. It has led to the extensive study of biometric technologies and the development of numerous algorithms, applications, and systems, which could be defined as Advanced Biometrics. This presentation will systematically explain this new research trend. As case studies, a new biometrics technology (palmprint recognition) and two new biometrics applications (medical biometrics and aesthetical biometrics) are introduced. Some useful achievements could be given to illustrate their effectiveness.

Brian Lovell

Professor, University of Queensland, Australia

Fellow of IAPR

  Biography:Brian C. Lovell was born in Brisbane, Australia in 1960. He received the BE in electrical engineering in 1982, the BSc in computer science in 1983, and the PhD in signal processing in 1991: all from the University of Queensland (UQ). Professor Lovell is Director of the Advanced Surveillance Group in the School of ITEE, UQ. He was President of the International Association for Pattern Recognition (IAPR) [2008-2010], and is Fellow of the IAPR, Senior Member of the IEEE, and voting member for Australia on the Governing Board of the IAPR. He is General Co-Chair of the International Conference on Biometrics (ICB2018) Gold Coast, Australia and was Program Co-Chair of the International Conference of Pattern Recognition (ICPR2016) in Cancún Mexico, and was General Co-Chair of the IEEE International Conference on Image Processing in Melbourne, 2013. His interests include non-cooperative Face Recognition, Surveillance, robust face detection, Biometrics, and Pattern Recognition. His work in biometrics and surveillance has won numerous international awards including the prestigious Best CCTV System at IFSEC2011, Birmingham for Face in the Crowd recognition. He also won the Asia Pacific ICT Trophy for Best R&D in the Asia Pacific Region in Phuket, Thailand in 2011.
     Title:Scalable biometric systems for banking and security
   Abstract: In this talk I will describe our research work on several huge real-world surveillance and biometric projects. One project is a federated transcontinental biometrics network with face recognition appliance nodes in Australia, UK, and Brazil. This fully operational system was piloted for the Olympic Games and ran securely over the internet with edge processing to massively reduce bandwidth requirements and improve privacy. The network was highly scalable to thousands of nodes as all communication was simply lightweight secure messages over the public internet. The federated cloud-based incident management application on Amazon Web Services is available to all users from anywhere in the world on a need to know basis. This state-of-the-art system required highly reliable robust CCTV–based video face recognition and I will discuss the huge technical challenges of simultaneous pose, expression, illumination, obscuration, artefact, and motion blur compensation. A huge system is currently operating as a reference site at Swinburne University of Technology with 16 simultaneous high-definition video streams and up to 178,000 persons in the watchlist. Such systems are easily extended with highly accurate mobile and wearable face recognition through Android and iOS mobile devices including the ODG R7 Augmented Reality Smart glasses. I will also discuss our related work in mobile banking applications and mobile 3D and 2 ½D face recognition on mobile phones. There will be live or video demonstrations or videos of mobile, cloud-based, and wearable biometric systems in real-time operation.