Secure Scalable CCTV, Mobile, and Wearable Video Face Recognition

Slides (pdf)Video


There has been a great deal of work on face recognition technologies over at least the last 35 years including some on video based recognition. In 16 years of research we have implemented and evaluated many state‐of‐the‐art systems, but almost all methods we have tested to date failed miserably when tested on uncontrolled low resolution image probes against uncontrolled low quality face galleries. Formal benchmarking on passport quality images will often yield impressive recognition rates with virtually zero errors. Yet everyone with any experience in biometrics knows that such performance is simply unattainable in the field without enormously expensive image capture equipment. Traditionally obtaining good recognition rates is all about getting the image capture conditions absolutely perfect — and achieving this in the field is incredibly expensive.

In this presentation I will describe our biometrics and surveillance research work on a transcontinental surveillance project currently running with multi-camera face recognition appliance nodes in Australia, UK, and Brazil. These systems runs securely over the internet with edge processing to massively reduce bandwidth requirements and to improve corporate privacy. There is no requirement for an expensive dedicated fibre network to connect all the high speed cameras - indeed wireless and mobile connectivity is often a viable option. The cloud-based incident management backbone is accessible to all users from anywhere in the world. Along the way I will discuss the basics of robust CCTV-based video face recognition and the huge technical challenges of simultaneous pose, expression, illumination, obscuration, and motion blur compensation. I will also discuss quite recent work on robust face detection, landmarking, and tracking which enables our systems to work on a crowd of people walking quickly past the cameras. There will be live demonstrations including of mobile and possibly wearable face recognition apps.


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. Professor Lovell is General Co-Chair of the International Conference on Biometrics to be held on the Gold Coast, Australia, in 2018. He was General Co‐Chair of the IEEE International Conference on Image Processing in Melbourne, 2013 and Program Co‐Chair of the International Conference of Pattern Recognition in Cancun, 2016. In 2011, the Face in the Crowd recognition system developed by his research group won the IFSEC Industrial Prize for Best CCTV System (Birmingham, UK) and the APICTA Trophy for Best R&D in the Asia‐Pacific Region (Phuket, Thailand). These early systems were also demonstrated to the research community during invited presentations at CVPR2011 (Colorado Springs) and IJCB2011 (Washington). His research interests include non‐cooperative and mobile Face Recognition, Biometrics, Surveillance, Statistical Manifolds, and Pattern Recognition. In 2016 his startup company was listed as a Top 20 Homeland Security Provider by US-based Government CIO Outlook Magazine.

Brian Lovell

Brian Lovell
The University of Queensland, Australia