The necessity and importance of accurate and reliable identification of human individuals cannot be overstated in our increasingly interconnected society. As traditional identification such as passwords cannot deliver the required accuracy and reliability, biometric identification (or simply biometrics) is widely seen as the promising alternative. This talk will review the latest progress of the most popular biometric modalities and figure out some promising research directions for the next generation biometrics. Focus will be given on our recent work on iris, face and gait recognition with some interesting demos such as mobile iris recognition, iris recognition at a distance, GAN (Generative Adversarial Networks）based face image super-resolution and photorealistic face rotation, cross-view gait recognition, etc.
Tieniu Tan received MSc and PhD degrees in electronic engineering from Imperial College London, U.K and received BSc degree in electronic engineering from Xi'an Jiaotong University, China. He returned to China in 1998 and joined the National Laboratory of Pattern Recognition (NLPR), Institute of Automation of the Chinese Academy of Sciences (CAS), Beijing, China, where he is currently a Professor and the director of Center for Research on Intelligent Perception and Computing (CRIPAC), and was former director (1998-2013) of the NLPR and Director General of the Institute (2000-2007). He is Member of the Chinese Academy of Sciences, International Fellow of the UK Royal Academy of Engineering, Fellow of The World Academy of Sciences for the advancement of sciences in developing countries (TWAS), Corresponding Member of the Brazilian Academy of Sciences, and Fellow of the IEEE and IAPR (International Association for Pattern Recognition). He is currently also Deputy Director of Liaison Office of the Central People's Government in the Hong Kong S.A.R. He has published 14 edited books or monographs and more than 600 research papers in refereed international journals and conferences in the areas of image processing, computer vision and pattern recognition. His current research interests include biometrics, computer vision and pattern recognition.