Trustworthy Biometrics Webinar

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With the diversity of biometric applications in our daily life, increasing attention has been paid to its security and trustworthiness. Many recent problems, such as deepfakes and adversarial attacks, pose new threats to existing biometric systems. Therefore, we establish Trustworthy Biometrics Webinar, supported by IEEE Beijing Section Biometrics Council Chapter, to provide an international platform for researchers who are concerned about biometrics and its security problems. We welcome more people from all over the world to join us, to explore more trustworthy biometrics in the future.



  Date and Time

  Location

  Hosts

  Registration



  • Date: 08 Jul 2021
  • Time: 08:00 PM to 09:00 PM
  • All times are Asia/Shanghai
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VooV/Tencent Meeting ID: 859 220 699

Link:

https://meeting.tencent.com/s/nE9H8UMj1zvI

  • Institute of Automation, Chinese Academy of Sciences
  • Beijing
  • China 100190

  • Co-sponsored by Institute of Automation, Chinese Academy of Sciences


  Speakers

Prof. Xiaoming Liu

Prof. Xiaoming Liu of Michigan State University

Topic:

On the Recent Development of Trustworthy Biometrics

In recent years we have witnessed increasingly diverse application scenarios of Biometrics in our daily life, despite the societal concerns on some of the weakness of the technology. A sustainable deployment and prospects of biometric systems will rely heavily on the ability to trust the recognition process and its output. As a result, in addition to the high recognition accuracy, trustworthy biometrics has become an emerging research area, with topics ranging from biometrics security (e.g., presentation attack detection and forgery detection), biasness in biometrics, adversarial robustness, to interpretable biometrics. In this talk, we will present some of the recent works on these topics and discuss the remaining issues warrant future research. 

Biography:

Dr. Xiaoming Liu is the MSU Foundation Professor at the Department of Computer Science and Engineering of Michigan State University (MSU). He received Ph.D. degree from Carnegie Mellon University in 2004. Before joining MSU in 2012 he was a research scientist at General Electric (GE) Global Research. He works on computer vision, machine learning, and biometrics especially on 3D vision, and facial analysis. Since 2012 he helps to develop a strong computer vision area in MSU who is ranked top 15 in US according to the 5-year statistics at csrankings.org. He received the 2018 Withrow Distinguished Scholar Award from MSU. He has been Area Chairs for numerous conferences, including CVPR, ICCV, ECCV, ICLR, NeurIPS, ICML, the Co-Program Chair of BTAS’18, WACV’18, and AVSS’21 conferences, and Co-General Chair of FG’23 conference. He is an Associate Editor of Pattern Recognition Letters, Pattern Recognition, and IEEE Transaction on Image Processing. He has authored more than 150 scientific publications, and has filed 29 U.S. patents. His work has been cited over 14000 times according to Google Scholar, with an H-index of 59. He is a fellow of IAPR. More information of Dr. Liu’s research can be found at http://cvlab.cse.msu.edu