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Professor Brian Lovell
Professor

Brian Lovell

Email: 
Phone: 
+61 7 336 54134

Overview

Background

Brian C. Lovell, born in Brisbane, Australia in 1960, received his BE in Electrical Engineering (Honours I) in 1982, BSc in Computer Science in 1983, and PhD in Signal Processing in 1991, all from the University of Queensland (UQ). Currently, he is the Project Leader of the Advanced Surveillance Group at UQ. Professor Lovell served as the President of the International Association of Pattern Recognition from 2008 to 2010, is a Senior Member of the IEEE, a Fellow of the IEAust, Fellow of the Asia-Pacific AI Association, and has been a voting member for Australia on the Governing Board of the International Association for Pattern Recognition since 1998.

He is an Honorary Professor at IIT Guwahati, India; an Associate Editor of the Pattern Recognition Journal; an Associate Editor-in-Chief of the Machine Learning Research Journal; a member of the IAPR TC4 on Biometrics; and a member of the Awards Committee and Education Committee of the IEEE Biometrics Council.

In addition, Professor Lovell has chaired and co-chaired numerous international conferences in the field of pattern recognition, including ICPR2008, ACPR2011, ICIP2013, ICPR2016, and ICPR2020. His Advanced Surveillance Group has collaborated with port, rail, and airport organizations, as well as several national and international agencies, to develop technology-based solutions for operational and security concerns.

His current research projects are in the fields of:

  • Artificial Intelligence
  • StyleGAN
  • Stable Diffusion
  • Deep Learning
  • Biometrics
  • Robust Face Recognition using Deep Learning
  • Masked Face Recognition for COVID-19 Pandemic
  • Adversarial Attacks on AI Systems
  • Digital Pathology
  • Neurofibroma Detection and Assessment
  • Object Detection with Deep Learning

I am actively recruiting PhD students in Artificial Intelligence to work with my team. If you are interested and have a strong record from a good university, with a publication in a good conference such as CVPR, ICCV, ECCV, or MICCAI please send your CV to me. Full Scholarships (Tuition and Living) can be awarded within one month for truly exceptional candidates.

Availability

Professor Brian Lovell is:
Available for supervision
Media expert

Qualifications

  • Bachelor (Honours) of Engineering, The University of Queensland
  • Bachelor of Science, The University of Queensland
  • Doctor of Philosophy, The University of Queensland

Research interests

  • Face Recognition with Deep Learning

    We develop new technologies to improve face recognition. Our group is first in the world to develop face recognition databases based entirely on synthetic faces. Other aspects of face recognition and affective computing (determining emotions from facial expressions) are current research themes within the group.

  • Object Detection Using Deep Learning

    We are researching improved techniques to identify small objects with high precision

  • Synthetic Face and Image Generation

    We were the first to investigate training face recognition systems on synthetic faces.

Research impacts

I have been pleased that my biometrics and other research has and is being been adopted commercially worldwide. My earlier face recognition systems have been installed by the University of San Francisco and Swinburne University among many other sites. More recently we have developed face recognition systems that are insensitive to the wearing of masks. These systems depend on our EDITH Ethical Face database of synthetic faces. To the best of our knowledge, we are the only group worldwide who can synthesise faces to order to train advanced ethical face recognition systems.

These systems have been adopted in the UK in 2020 by Facewatch Ltd and are currently being considered by the UK National Health Service and also Queensland Health to manage COVID 19 quarantine facilities and border control. In 2020-2021 we developed a touchless face mask fitting system for health workers to reduce the wastage of PPE and improve COVID19 management. This system is deployed on Queensland Health IT infrastructure in February 2021 and is planned to be made available nationally and internationally. The system has the potential to save millions of dollars in wasted PPE.

PRIZES, HONOURS AND AWARDS

Fellow of the IAPR, 2008 Multiple Best Paper prizes. Awarded Certificate of Recognition as most downloaded author at UQ by UQCybrary. Over 26,000 copies of my research papers were downloaded from the UQ EPrints archive in the 12 months ending May, 2005. APICTA Trophy for Best Research and Development, 2011, Face Recognition in a Crowd IFSEC Trophy 2011, Best CCTV Product of the Year (excluding cameras and lens), Face Recognition in a Crowd Technology Winner, ADS Security Innovation Award, 2021, Galahad facial detection and recognition software, awarded by the UK Home Office at the Security and Policing Show on March 9, 2021.

Works

Search Professor Brian Lovell’s works on UQ eSpace

355 works between 1988 and 2025

221 - 240 of 355 works

2009

Conference Publication

Fusion of hand based biometrics using ant colony optimization

Madasu, Vamsi K., Lovell, Brian C. and Vasikarla, Shantaram (2009). Fusion of hand based biometrics using ant colony optimization. AIPR 2009. Vision: Humans, Animals, and Machines. 38th Applied Imagery Pattern Recognition Workshop, Washington, DC, U.S.A., 14-16 October 2009.

Fusion of hand based biometrics using ant colony optimization

2009

Conference Publication

Exploiting Bayesian belief network for adaptive IP-reuse decision

Azman, A. W., Bigdeli, A., Biglari-Abhari, M., Mustafah, Y. M. and Lovell, B. C. (2009). Exploiting Bayesian belief network for adaptive IP-reuse decision. Digital Image Computing: Techniques and Applications, DICTA 2009, Melbourne, VIC Australia, 1 - 3 December 2009. Piscataway, NJ United States: I E E E. doi: 10.1109/DICTA.2009.21

Exploiting Bayesian belief network for adaptive IP-reuse decision

2009

Conference Publication

Face Detection System Design for Real Time High Resolution Smart Camera

Mustafah, Yasir M., Bigdeli, Abbas, Azman, Amelia W. and Lovell, Brian C. (2009). Face Detection System Design for Real Time High Resolution Smart Camera. 3rd ACM/IEEE International Conference on Distributed Smart Cameras, Como Italy, Aug 30-Sep 02, 2009. NEW YORK: IEEE.

Face Detection System Design for Real Time High Resolution Smart Camera

2009

Book Chapter

Intelligent CCTV for mass transport security: Challenges and opportunities for video and face processing

Sanderson, Conrad, Bigdeli, Abbas, Shan, Ting, Chen, Shaokang, Berglund, Erik and Lovell, Brian C. (2009). Intelligent CCTV for mass transport security: Challenges and opportunities for video and face processing. Progress in Computer Vision and Image Analysis. (pp. 557-573) edited by Horst Bunke, Juan José Villanueva, Gemma Sánchez and Xavier Otazu. Singapore: World Scientific. doi: 10.1142/9789812834461_0030

Intelligent CCTV for mass transport security: Challenges and opportunities for video and face processing

2008

Journal Article

Formation and evolution of the ionospheric plasma density shoulder and its relationship to the superfountain effects investigated during the 6 November 2001 great storm

Horvath, Ildiko and Lovell, Brian C. (2008). Formation and evolution of the ionospheric plasma density shoulder and its relationship to the superfountain effects investigated during the 6 November 2001 great storm. Journal of Geophysical Research, 113 (12 Article - A12315) A12315, 1-17. doi: 10.1029/2008JA013153

Formation and evolution of the ionospheric plasma density shoulder and its relationship to the superfountain effects investigated during the 6 November 2001 great storm

2008

Conference Publication

On Intelligent Surveillance Systems and Face Recognition for Mass Transport Security

Lovell, Brian C., Chen, Shaokang, Bigdeli, Abbas, Berglund, Erik and Sanderson, Conrad (2008). On Intelligent Surveillance Systems and Face Recognition for Mass Transport Security. International Conference on Control, Automation, Robotics and Vision (ICARCV), 2008., Hanoi, Vietnam, 17 - 20 December 2008. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICARCV.2008.4795605

On Intelligent Surveillance Systems and Face Recognition for Mass Transport Security

2008

Book Chapter

Real-time face detection and classification for ICCTV

Lovell, Brian C., Chen, Shaokang and Shan, Ting (2008). Real-time face detection and classification for ICCTV. Encyclopedia of Data Warehousing and Mining. (pp. 1-19) edited by John Wang. Hershey, PA: Information Science Reference.

Real-time face detection and classification for ICCTV

2008

Conference Publication

Proceedings of the 1st International Conference on Advances in Computer-Human Interaction, ACHI 2008: Preface

Dascalu, Sergiu, Wang, Alf Inge, Dragan, Irinel C., Ge, Shuzhi Sam, Nakashima, Tomoharu, Milani, Alfredo, Lovell, Brian C., Viniotis, Yannis, Latombe, Jean-Claude, Nearchou, Andreas C., Oinas-Kukkonen, Harri and Zaytoon, Janan (2008). Proceedings of the 1st International Conference on Advances in Computer-Human Interaction, ACHI 2008: Preface. First International Conference on Advances in Computer-Human Interaction, Saint Luce, Martinique, 10-15 February 2008. doi: 10.1109/ACHI.2008.4

Proceedings of the 1st International Conference on Advances in Computer-Human Interaction, ACHI 2008: Preface

2008

Conference Publication

Fuzzy Co-Clustering of Medical Images using Bacterial Foraging

Hanmandlu, M., Susan, S., Madasu, V.K. and Lovell, B.C. (2008). Fuzzy Co-Clustering of Medical Images using Bacterial Foraging. Image and Vision Computing New Zealand 2008, Lincoln University, New Zealand, 26-28 November, 2008. USA: IEEE. doi: 10.1109/IVCNZ.2008.4762136

Fuzzy Co-Clustering of Medical Images using Bacterial Foraging

2008

Book Chapter

Robust face recognition technique for a real-time embedded face recognition system

Shan, Ting, Bigdeli, Abbas, Lovell, Brian C. and Chen, Shaokang (2008). Robust face recognition technique for a real-time embedded face recognition system. Pattern recognition technologies and applications : Recent advances. (pp. 188-211) edited by Brijesh Verma and Michael Blumenstein. Hershey, PA, U.S.A.: Information Science Reference. doi: 10.4018/978-1-59904-807-9.ch008

Robust face recognition technique for a real-time embedded face recognition system

2008

Conference Publication

A high resolution smart camera with GigE Vision extension for surveillance applications

Norouznezhad, E., Bigdeli, A., Postula, A. and Lovell, B. C. (2008). A high resolution smart camera with GigE Vision extension for surveillance applications. 2nd ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC’08), Palo Alto, CA, U.S.A., 7-11 September 2008. Piscataway, NJ, U.S.A.: IEEE Xplore. doi: 10.1109/ICDSC.2008.4635711

A high resolution smart camera with GigE Vision extension for surveillance applications

2008

Book

Bézier and splines in image processing and machine vision

Biswas, Sambhunath and Lovell, Brian C. (2008). Bézier and splines in image processing and machine vision. London, U.K.: Springer.

Bézier and splines in image processing and machine vision

2008

Book Chapter

An Automatic Offline Signature and Forgery Detection System

Madasu, Vamsi Krishna and Lovell, Brian C. (2008). An Automatic Offline Signature and Forgery Detection System. Pattern recognition technologies and applications : Recent advances. (pp. 63-89) edited by Brijesh Verma and Michael Blumenstein. Hersey, PA: Information Science Reference. doi: 10.4018/978-1-59904-807-9.ch004

An Automatic Offline Signature and Forgery Detection System

2008

Conference Publication

Tracking with Multiple Cameras for Video Surveillance

Bhuyan, M. K., Lovell, B. C. and Bigdeli, A. (2008). Tracking with Multiple Cameras for Video Surveillance. 9th Biennial Conference of the Australian Pattern Recognition Society, Glenelg, SA, Australia, 3-5 December 2007. Glenelg, SA, Australia: IEEE Computer Society. doi: 10.1109/DICTA.2007.4426852

Tracking with Multiple Cameras for Video Surveillance

2008

Conference Publication

Experimental analysis of face recognition on still and CCTV images

Chen, Shaokang, Berglund, Erik, Bigdeli, Abbas, Sanderson, Conrad and Lovell, Brian C. (2008). Experimental analysis of face recognition on still and CCTV images. IEEE International Conference on Advanced Video and Signal Based Surveillance 2008 (AVSS '08), Santa Fe, New Mexico, U.S.A., 1-3 September 2008. Piscataway, NJ, United States: IEEE - Institute of Electrical Electronics Engineers Inc.. doi: 10.1109/AVSS.2008.15

Experimental analysis of face recognition on still and CCTV images

2008

Book Chapter

Robust Face recognition for Data Mining

Lovell, Brian C. and Chen, Shaokang (2008). Robust Face recognition for Data Mining. Data Warehousing and Mining: Concepts, Methodologies, Tools and Applications. (pp. 3621-3629) edited by John Wang. Hershey, PA: Information Science Reference.

Robust Face recognition for Data Mining

2007

Book Chapter

Support vector machines for business applications

Lovell, Brian C. and Walder, Christian J. (2007). Support vector machines for business applications. Mathematical Methods for Knowledge Discovery and Data Mining. (pp. 82-100) IGI Global. doi: 10.4018/978-1-59904-528-3.ch005

Support vector machines for business applications

2007

Conference Publication

Real-time face detection and tracking for high resolution smart camera system

Mustafah, Y. M., Shan, T., Azman, A., Bigdeli, A. and Lovell, B. C. (2007). Real-time face detection and tracking for high resolution smart camera system. 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA 2007), Adelaide, Australia, 3-5 December 2007. Piscataway, NJ, U.S.A.: IEEE - Institute of Electrical Electronics Engineers Inc.. doi: 10.1109/DICTA.2007.4426823

Real-time face detection and tracking for high resolution smart camera system

2007

Conference Publication

Smart cameras enabling automated face recognition in the crowd for intelligent surveillance system

Mustafah, Y.M., Bigdeli, A., Azman, A.W and Lovell, B.C. (2007). Smart cameras enabling automated face recognition in the crowd for intelligent surveillance system. Recent Advances in Security Technology (RNSA) 2007, Melbourne, Australia, 28 September, 2007. Curtin, ACT: Australian Homeland Security Research Centre.

Smart cameras enabling automated face recognition in the crowd for intelligent surveillance system

2007

Conference Publication

Face Detection on Embedded Systems

Bigdeli, Abbas, Sim, Colin, Biglari-Abhari, Morteza and Lovell Brian C. (2007). Face Detection on Embedded Systems. Third International Conference on Embedded Software and Systems, Daegu, Korea, 14-16 May 2007. Berlin, Heidelberg: Springer-Verlag. doi: 10.1007/978-3-540-72685-2_28

Face Detection on Embedded Systems

Funding

Current funding

  • 2024 - 2029
    Application of AI/Machine Learning, computer vision and automated systems
    UniQuest Pty Ltd
    Open grant
  • 2024 - 2026
    The Neurofibromatosis type 1 (NF1) Cutaneous Neurofibroma Consortium: Identifying Genetic modifiers of disease burden to inform treatment pathways (MRFF Neurofibromatosis led by Uni Newcastle)
    University of Newcastle
    Open grant

Past funding

  • 2021 - 2025
    UQAI Scholarship
    AR Live Systems Ltd
    Open grant
  • 2020 - 2021
    N95 Mask Fitment
    Queensland Health
    Open grant
  • 2019 - 2021
    AR Live Face Recognition and AI Project
    AR Live Systems Ltd
    Open grant
  • 2019 - 2021
    Justified Autonomous Unmanned Aerial System Effect (Defence CRC for Trusted Autonomous Systems project led by Skyborne Technologies Pty Ltd)
    Skyborne Technologies Pty Ltd
    Open grant
  • 2019
    Development of a standalone program for the automation of quantitative fractography - 2
    Commonwealth Defence Science and Technology Group
    Open grant
  • 2019
    Expanding Wiener, a high performance GPU cluster
    UQ Research Facilities Infrastructure Grants
    Open grant
  • 2018 - 2020
    Digitisation and image recognition in environmental chemistry
    UniQuest Pty Ltd
    Open grant
  • 2017 - 2022
    Fusion of Digital Microscopy and Plain Text Reports for Automated Analysis
    ARC Linkage Projects
    Open grant
  • 2017 - 2018
    Further development of a demonstrator for the automation of quantitative fractography
    Commonwealth Defence Science and Technology Group
    Open grant
  • 2017 - 2019
    Vision based automated corrosion analysis for galvanised steel lattice towers
    UniQuest Pty Ltd
    Open grant
  • 2016 - 2017
    Development of a demonstrator for the automation of quantitative fractography
    Commonwealth Defence Science and Technology Group
    Open grant
  • 2015
    ILC Coal Carry Back Project
    Australian Mathematical Sciences Institute Industry Internship Program
    Open grant
  • 2014 - 2015
    AMSI computer vision project
    Australian Mathematical Sciences Institute Industry Internship Program
    Open grant
  • 2013 - 2017
    Application of manifold-based image analysis to identify subtle changes in digitally-captured pathology samples
    ARC Linkage Projects
    Open grant
  • 2013
    AMSI Internship Program - Vehicle number plate identification
    Australian Mathematical Sciences Institute Industry Internship Program
    Open grant
  • 2013 - 2014
    Investigating repeatable ionospheric features during large space storms and superstorms
    United States Asian Office of Aerospace Research and Development
    Open grant
  • 2012 - 2016
    Forensic reasoning and uncertainty: Identifying pattern and impression expertise
    ARC Linkage Projects
    Open grant
  • 2011 - 2013
    Baseline Rail Level Crossing Video (R2.119)
    CRC for Rail Innovation
    Open grant
  • 2010 - 2012
    Assessing error in forensic identification: The development of scientific and legal standards of evidence
    UQ Collaboration and Industry Engagement Fund
    Open grant
  • 2007 - 2009
    Markov field theory applied to sensor networks analysis and design (ARC DP0772218 administered by University of South Australia)
    University of South Australia
    Open grant
  • 2006 - 2008
    Intelligent Closed Circuit TV (ICCTV) project
    National ICT Australia Ltd (NICTA)
    Open grant
  • 2004
    ARC Network in Imaging Science and Technology
    ARC Seed Funding for Research Networks
    Open grant
  • 1996
    Development of metrics for texture classification algorithms
    University of Queensland New Staff Research Grant
    Open grant

Supervision

Availability

Professor Brian Lovell is:
Available for supervision

Before you email them, read our advice on how to contact a supervisor.

Supervision history

Current supervision

  • Doctor Philosophy

    Advanced Strategies to Alleviate Challenges of Data Scarcity in Deep Learning for Medical Image Analysis

    Principal Advisor

    Other advisors: Associate Professor Marcus Gallagher

  • Doctor Philosophy

    Out-of-Distribution Generalisation and Detection in Feature Embedding Space

    Principal Advisor

    Other advisors: Associate Professor Mahsa Baktashmotlagh

  • Doctor Philosophy

    Pose Estimation for Human with Disabilities

    Associate Advisor

    Other advisors: Dr Xin Yu

  • Doctor Philosophy

    Generating data-driven continuous optimization problems for benchmarking

    Associate Advisor

    Other advisors: Associate Professor Marcus Gallagher

  • Doctor Philosophy

    Modelling cloud movement to generate short term solar irradiance predictions and subsequent expected PV power production

    Associate Advisor

    Other advisors: Professor Eve McDonald-Madden, Dr Hui Ma

Completed supervision

Media

Enquiries

Contact Professor Brian Lovell directly for media enquiries about:

  • Artificial Intelligence
  • Biometrics
  • Border control
  • Computer modelling
  • Computer vision
  • Deep Learning
  • Face Recognition
  • Face-recognition technology
  • Identification technology
  • Image processing
  • Information technology
  • National security surveillance
  • Networks - neural
  • Neural networks - artificial
  • Pattern Recognition
  • Pattern recognition - digital imaging
  • Signal Processing
  • Wearable Technologies

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