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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

301 - 320 of 355 works

2003

Conference Publication

A closed form solution to the reconstruction and multi-view constraints of the degree d apparant contour

McKinnon, D. N. R., Jones, B. D. and Lovell, B. C. (2003). A closed form solution to the reconstruction and multi-view constraints of the degree d apparant contour. The 2003 APRS Workshop on Digital Image Computing, Brisbane, 7 February, 2003. Brisbane: Australian Pattern Recognition Society.

A closed form solution to the reconstruction and multi-view constraints of the degree d apparant contour

2003

Conference Publication

Face Recognition with One Sample Image per Class

Chen, Shaokang and Lovell, Brian C. (2003). Face Recognition with One Sample Image per Class. Australian and New Zealand Intelligent Information Systems, Sydney, 10-12 December. Brisbane: Queensland University of Technology.

Face Recognition with One Sample Image per Class

2003

Conference Publication

OFCat: An Extensible GUI-Driven Optical Flow Comparison Tool

Andrews, Robert J. and Lovell, Brian C. (2003). OFCat: An Extensible GUI-Driven Optical Flow Comparison Tool. The 2003 APRS Workshop on Digital Image Computing, Brisbane, 7 February, 2003. Brisbane: Australian Pattern Recognition Society.

OFCat: An Extensible GUI-Driven Optical Flow Comparison Tool

2003

Conference Publication

Kernel Based Algebraic Curve Fitting

Walder, Christian J. and Lovell, Brian C. (2003). Kernel Based Algebraic Curve Fitting. International Conference on Advances in Pattern Recogntion, Calcutta, 10-13 December. Kolkata: Allied Publishers.

Kernel Based Algebraic Curve Fitting

2003

Edited Outputs

Proceedings of the 2003 APRS Workshop on Digital Image Computing

Brian C. Lovell and Anthony, J. Maeder eds. (2003). Proceedings of the 2003 APRS Workshop on Digital Image Computing. The 2003 APRS Workshop on Digital Image Computing (WDIC 2003), Brisbane, Queensland, 7 February, 2003. Brisbane, Queensland: The Australian Pattern Recognition Society.

Proceedings of the 2003 APRS Workshop on Digital Image Computing

2003

Conference Publication

Polytopes, Feasible Regions and Occlusions in the n-view Reconstruction Problem

McKinnon, David, Jones, Barry and Lovell, Brian C. (2003). Polytopes, Feasible Regions and Occlusions in the n-view Reconstruction Problem. Workshop on Digital Image Computing, Brisbane, 7 February, 2003. Brisbane, Australia: Australian Pattern Recognition Society.

Polytopes, Feasible Regions and Occlusions in the n-view Reconstruction Problem

2003

Conference Publication

Autonomous Direct 3D Segmentation of Articular Knee Cartilage

Hinrichs, Enrico, Appleton, Ben, Lovell, Brian C. and Galloway, Graham John (2003). Autonomous Direct 3D Segmentation of Articular Knee Cartilage. Australian and New Zealand Intelligent Information Systems, Sydney, Australia, 10-12 December, 2003. Brisbane, Qld: Queensland University of Technology.

Autonomous Direct 3D Segmentation of Articular Knee Cartilage

2002

Conference Publication

Improved Classification Using Hidden Markov Averaging From Multiple Observation Sequences

Davis, R. I. A., Walder, C. J. and Lovell, Brian C. (2002). Improved Classification Using Hidden Markov Averaging From Multiple Observation Sequences. Fourth Australasian Workshop on Signal Processing and Applications 2002, Brisbane, 17-18 December, 2002. Brisbane: Queensland University of Technology.

Improved Classification Using Hidden Markov Averaging From Multiple Observation Sequences

2002

Conference Publication

General Purpose Real-Time Object Tracking using Hausdorff Transforms

Vignon, D., Lovell, Brian C. and Andrews, Robert J. (2002). General Purpose Real-Time Object Tracking using Hausdorff Transforms. 9th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Annency, France, 1-5 July, 2002. France: ESIA.

General Purpose Real-Time Object Tracking using Hausdorff Transforms

2002

Conference Publication

Low-cost real-time gesture recognition

Lovell, B. C. and Heckenberg, D. R. (2002). Low-cost real-time gesture recognition. Digital Image Computing Techniques and Applications, Melbourne, 21-22 January, 2002. Melbourne: APRS.

Low-cost real-time gesture recognition

2002

Conference Publication

Improved estimation of hidden Markov model parameters from multiple observation sequences

Davis, Richard I. A., Lovell, Brian C. and Caelli, Terry (2002). Improved estimation of hidden Markov model parameters from multiple observation sequences. International Conference on Pattern Recognition, Quebec City, Canada, 11-15 August, 2002. The Institute of Electrical and Electronics Engineers. doi: 10.1109/icpr.2002.1048264

Improved estimation of hidden Markov model parameters from multiple observation sequences

2002

Conference Publication

Portable VXL system for computing structure from motion

Mckinnon, D., Kubik, K. K. T. and Lovell, B. C. (2002). Portable VXL system for computing structure from motion. Digital Image Computing Techniques and Applications, Melbourne, 21-22 January, 2002. Melbourne: APRS.

Portable VXL system for computing structure from motion

2002

Conference Publication

Low-Cost Real-Time Gesture Recognition

Lovell, Brian C. and Heckenberg, Daniel (2002). Low-Cost Real-Time Gesture Recognition. ACCV2002, 22-25 January, 2002.

Low-Cost Real-Time Gesture Recognition

2002

Conference Publication

Face Recognition with APCA in Variant Illuminations

Chen, S., Lovell, B. C. and Sun, S. (2002). Face Recognition with APCA in Variant Illuminations. Fourth Australasian Workshop on Signal Processing and Applications 2002, Brisbane, 17-18 December, 2002. Brisbane: Queensland University of Technology.

Face Recognition with APCA in Variant Illuminations

2002

Conference Publication

Real-time Hausdorff-based tracking

Vignon, D. and Lovell, B. C. (2002). Real-time Hausdorff-based tracking. Digital Image Computing Techniques and Applications, Melbourne, 21-22 January, 2002. Melbourne: APRS.

Real-time Hausdorff-based tracking

2002

Conference Publication

Face and Object Recognition and Detection Using Colour Vector Quantisation

Walder, C. J. and Lovell, B. C. (2002). Face and Object Recognition and Detection Using Colour Vector Quantisation. Fourth Australasian Workshop on Signal Processing and Applications 2002, Brisbane, 17-18 December, 2002. Brisbane: Queensland University of Technology.

Face and Object Recognition and Detection Using Colour Vector Quantisation

2002

Conference Publication

Real-time two hands tracking system

Liu, N. and Lovell, B. C. (2002). Real-time two hands tracking system. The 2002 International Technical Conference on Circuits, Systems, Computers and Communications, Phuket, Thailand, 16-19 July, 2002. Thonburi, Thailand: King Mongkut's University of Technology.

Real-time two hands tracking system

2001

Conference Publication

Method for Accurate Unsupervised Cell Nucleus Segmentation

Bamford, Pascal and Lovell, Brian C. (2001). Method for Accurate Unsupervised Cell Nucleus Segmentation. IEEE Engineering in Medicine and Biology, Istanbul, Turkey, 25-28 October, 2001. Piscataway, New Jersey: IEEE.

Method for Accurate Unsupervised Cell Nucleus Segmentation

2001

Conference Publication

Real-time MMX-accelerated image stabilization system

Chen, S. and Lovell, B. C. (2001). Real-time MMX-accelerated image stabilization system. Image and Vision Computing 2001, Dunedin, New Zealand, 26-28 November, 2001. Dunedin, New Zealand: Wickliffe Limited.

Real-time MMX-accelerated image stabilization system

2001

Conference Publication

Real-Time MMX-Accelerated Image Stabilization System

Chen, Shaokang and Lovell, Brian C. (2001). Real-Time MMX-Accelerated Image Stabilization System. IVCNZ2001, Dunedin, New Zealand, 26-28 November, 2001.

Real-Time MMX-Accelerated Image Stabilization System

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

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Supervision history

Current supervision

  • Doctor Philosophy

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

    Principal Advisor

    Other advisors: Associate Professor Mahsa Baktashmotlagh

  • 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

    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

Need help?

For help with finding experts, story ideas and media enquiries, contact our Media team:

communications@uq.edu.au