Professor Brian Lovell
Professor

Brian Lovell

Email: 
Phone: 
+61 7 336 54134

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

Fields of research

Artificial intelligence Computer vision Computer vision and multimedia computation Engineering Image processing Information and Computing Sciences Pattern recognition

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.

Search Professor Brian Lovell’s works on UQ eSpace

355 works between 1988 and 2025
All (355) Journal Article (104) Book Chapter (19) Conference Publication (222) Book (1) Other Outputs (3) Edited Outputs (6)

121 - 140 of 355 works

2014

Conference Publication

Message from general and technical co-chairs

Lovell, Brian C. and Vento, Mario (2014). Message from general and technical co-chairs. 1st Workshop on Pattern Recognition Techniques for Indirect Immunofluorescence Images, Stockholm, Sweden, 24 August 2014. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/I3A.2014.4

Message from general and technical co-chairs

2014

Journal Article

Discriminative non-linear stationary subspace analysis for video classification

Baktashmotlagh, Mahsa, Harandi, Mehrtash, Lovell, Brian C. and Salzmann, Mathieu (2014). Discriminative non-linear stationary subspace analysis for video classification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36 (12) 6857376, 2353-2366. doi: 10.1109/TPAMI.2014.2339851

Discriminative non-linear stationary subspace analysis for video classification

2014

Journal Article

Perturbation electric fields and disturbance currents investigated during the 25 September 1998 great storm

Horvath, Ildiko and Lovell, Brian C. (2014). Perturbation electric fields and disturbance currents investigated during the 25 September 1998 great storm. Journal of Geophysical Research-Space Physics, 119 (10), 8483-8498. doi: 10.1002/2014JA020480

Perturbation electric fields and disturbance currents investigated during the 25 September 1998 great storm

2014

Journal Article

Visual learning and classification of human epithelial type 2 cell images through spontaneous activity patterns

Yang, Yan, Wiliem, Arnold, Alavi, Azadeh, Lovell, Brian C. and Hobson, Peter (2014). Visual learning and classification of human epithelial type 2 cell images through spontaneous activity patterns. Pattern Recognition, 47 (7), 2325-2337. doi: 10.1016/j.patcog.2013.10.013

Visual learning and classification of human epithelial type 2 cell images through spontaneous activity patterns

2014

Conference Publication

Classifying anti-nuclear antibodies HEp-2 images: A benchmarking platform

Hobson, Peter, Lovell, Brian C., Percannella, Gennaro, Vento, Mario and Wiliem, Arnold (2014). Classifying anti-nuclear antibodies HEp-2 images: A benchmarking platform. 22nd International Conference on Pattern Recognition, ICPR 2014, Stockholm, Sweden, 24 - 28 August 2014. Washington, DC United States: I E E E Computer Society. doi: 10.1109/ICPR.2014.557

Classifying anti-nuclear antibodies HEp-2 images: A benchmarking platform

2014

Conference Publication

Matching image sets via adaptive multi convex hull

Chen, Shaokang, Wiliem, Arnold, Sanderson, Conrad and Lovell, Brian C. (2014). Matching image sets via adaptive multi convex hull. IEEE Winter Conference on Applications of Computer Vision (WACV 2014), Steamboat Springs, CO, United States, 24-26 March 2014. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/WACV.2014.6835985

Matching image sets via adaptive multi convex hull

2014

Book Chapter

Secure face recognition for mobile applications

Lovell, Brian C. and Smith, Daniel F. (2014). Secure face recognition for mobile applications. Face Recognition in Adverse Conditions. (pp. 359-386) edited by Maria de Marsico, Michele Nappi and Massimo Tistarelli. Hershey, United States: Hershey Information Science Reference. doi: 10.4018/978-1-4666-5966-7.ch017

Secure face recognition for mobile applications

2014

Journal Article

Large plasma density enhancements occurring in the northern polar region during the 6 April 2000 superstorm

Horvath, Ildiko and Lovell, Brian C. (2014). Large plasma density enhancements occurring in the northern polar region during the 6 April 2000 superstorm. Journal of Geophysical Research A: Space Physics, 119 (6), 4805-4818. doi: 10.1002/2014JA019917

Large plasma density enhancements occurring in the northern polar region during the 6 April 2000 superstorm

2014

Journal Article

Fisher tensors for classifying human epithelial cells

Faraki, Masoud, Harandi, Mehrtash T., Wiliem, Arnold and Lovell, Brian C. (2014). Fisher tensors for classifying human epithelial cells. Pattern Recognition, 47 (7), 2348-2359. doi: 10.1016/j.patcog.2013.10.011

Fisher tensors for classifying human epithelial cells

2014

Conference Publication

Discovering discriminative cell attributes for HEp-2 specimen image classification

Wiliem, Arnold, Hobson, Peter and Lovell, Brian C. (2014). Discovering discriminative cell attributes for HEp-2 specimen image classification. IEEE Winter Conference on Applications of Computer Vision (WACV 2014), Steamboat Springs, CO, United States, 24-26 March 2014. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/WACV.2014.6836071

Discovering discriminative cell attributes for HEp-2 specimen image classification

2014

Conference Publication

Multi-Action Recognition via Stochastic Modelling of Optical Flow and Gradients

Carvajal, Johanna, Sanderson, Conrad, McCool, Chris and Lovell, Brian C. (2014). Multi-Action Recognition via Stochastic Modelling of Optical Flow and Gradients. MLSDA 2014 2nd Workshop on Machine Learning for Sensory Data Analysis, Gold Coast , QLD, Australia, 2 December 2014. New York, NY USA: ACM. doi: 10.1145/2689746.2689748

Multi-Action Recognition via Stochastic Modelling of Optical Flow and Gradients

2014

Conference Publication

Random projections on manifolds of symmetric positive definite matrices for image classification

Alavi, Azadeh, Wiliem, Arnold, Zhao, Kun, Lovell, Brian C. and Sanderson, Conrad (2014). Random projections on manifolds of symmetric positive definite matrices for image classification. IEEE Winter Conference on Applications of Computer Vision (WACV 2014), Steamboat Springs, CO, United States, 24-26 March 2014. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/WACV.2014.6836085

Random projections on manifolds of symmetric positive definite matrices for image classification

2014

Journal Article

Automatic classification of Human Epithelial type 2 cell Indirect Immunofluorescence images using Cell Pyramid Matching

Wiliem, Arnold, Sanderson, Conrad, Wong, Yongkang, Hobson, Peter, Minchin, Rodney F. and Lovell, Brian C. (2014). Automatic classification of Human Epithelial type 2 cell Indirect Immunofluorescence images using Cell Pyramid Matching. Pattern Recognition, 47 (7), 2315-2324. doi: 10.1016/j.patcog.2013.10.014

Automatic classification of Human Epithelial type 2 cell Indirect Immunofluorescence images using Cell Pyramid Matching

2014

Conference Publication

Domain adaptation on the statistical manifold

Baktashmotlagh, Mahsa, Harandi, Mehrtash T., Lovell, Brian C. and Salzmann, Mathieu (2014). Domain adaptation on the statistical manifold. 27th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2014, Columbus, OH, United States, 23-28 June 2014. Piscataway, NJ, United States: I E E E Computer Society. doi: 10.1109/CVPR.2014.318

Domain adaptation on the statistical manifold

2014

Conference Publication

Object tracking via non-Euclidean geometry: A Grassmann approach

Shiraz, Sareh, Harandi, Mehrtash T., Lovell, Brian C. and Sanderson, Conrad (2014). Object tracking via non-Euclidean geometry: A Grassmann approach. IEEE Winter Conference on Applications of Computer Vision (WACV 2014), Steamboat Springs, CO, United States, 24-26 March 2014. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/WACV.2014.6836008

Object tracking via non-Euclidean geometry: A Grassmann approach

2014

Conference Publication

Automatic image attribute selection for zero-shot learning of object categories

Liu, Liangchen, Wiliem, Arnold, Chen, Shaokang and Lovell, Brian C. (2014). Automatic image attribute selection for zero-shot learning of object categories. 22nd International Conference on Pattern Recognition, ICPR 2014, Stockholm, Sweden, 24-28 August, 2014. Washington, DC, United States: I E E E Computer Society. doi: 10.1109/ICPR.2014.452

Automatic image attribute selection for zero-shot learning of object categories

2013

Journal Article

Dynamically Adaptive Control System for Bioanodes in Serially Stacked Bioelectrochemical Systems

Andersen, Stephen J., Pikaar, Ilje, Freguia, Stefano, Lovell, Brian C., Rabaey, Korneel and Rozendal, Rene A. (2013). Dynamically Adaptive Control System for Bioanodes in Serially Stacked Bioelectrochemical Systems. Environmental Science and Technology, 47 (10), 5488-5494. doi: 10.1021/es400239k

Dynamically Adaptive Control System for Bioanodes in Serially Stacked Bioelectrochemical Systems

2013

Journal Article

Improved foreground detection via block-based classifier cascade with probabilistic decision integration

Reddy, Vikas, Sanderson, Conrad and Lovell, Brian (2013). Improved foreground detection via block-based classifier cascade with probabilistic decision integration. IEEE Transactions On Circuits And Systems For Video Technology, 23 (1) 6213100, 83-93. doi: 10.1109/TCSVT.2012.2203199

Improved foreground detection via block-based classifier cascade with probabilistic decision integration

2013

Book Chapter

Motion estimation in colour image sequences

Benois-Pineau, Jenny, Lovell, Brian C. and Andrews, Robert J. (2013). Motion estimation in colour image sequences. Advanced color image processing and analysis. (pp. 377-395) edited by Christine Fernandez-Maloigne. New York, NY, United States: Springer. doi: 10.1007/978-1-4419-6190-7_11

Motion estimation in colour image sequences

2013

Conference Publication

Improved image set classification via joint sparse approximated nearest subspaces

Chen, Shaokang, Sanderson, Conrad, Harandi, Mehrtash T and Lovell, Brian C. (2013). Improved image set classification via joint sparse approximated nearest subspaces. 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2013, Portland, OR United States, 23 - 28 June 2013. Piscataway, NJ United States: I E E E. doi: 10.1109/CVPR.2013.65

Improved image set classification via joint sparse approximated nearest subspaces

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

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

    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

    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

  • Doctor Philosophy

    Pose Estimation for Human with Disabilities

    Associate Advisor

    Other advisors: Dr Xin Yu

Completed supervision

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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