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)

161 - 180 of 355 works

2012

Conference Publication

Kernel analysis over Riemannian manifolds for visual recognition of actions, pedestrians and textures

Harandi, Mehrtash T., Sanderson, Conrad, Wiliem, Arnold and Lovell, Brian C. (2012). Kernel analysis over Riemannian manifolds for visual recognition of actions, pedestrians and textures. 2012 IEEE Workshop on Applications of Computer Vision, Breckenridge, CO, United States, 9-11 January 2012. Piscataway, NJ, United States: IEEE (Institute for Electrical and Electronic Engineers). doi: 10.1109/WACV.2012.6163005

Kernel analysis over Riemannian manifolds for visual recognition of actions, pedestrians and textures

2012

Conference Publication

Improved person re-identification using statistical approximation

Yang, Yan, Dadgostar, Farhad, Mau, Sandra and Lovell, Brian C. (2012). Improved person re-identification using statistical approximation. 2012 International Conference on Digital Image Computing: Techniques and Applications (DICTA), Fremantle, WA, Australia, 3-5 December 2012. Piscataway, NJ, United States: IEEE. doi: 10.1109/DICTA.2012.6411683

Improved person re-identification using statistical approximation

2012

Conference Publication

K-tangent spaces on Riemannian manifolds for improved pedestrian detection

Sanin, Andres, Sanderson, Conrad, Harandi, Mehrtash and Lovell, Brian C. (2012). K-tangent spaces on Riemannian manifolds for improved pedestrian detection. 2012 19th IEEE International Conference on Image Processing (ICIP), Orlando, United States, 30 September - 3 October 2012. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICIP.2012.6466899

K-tangent spaces on Riemannian manifolds for improved pedestrian detection

2012

Conference Publication

Sparse coding and dictionary learning for symmetric positive definite matrices: a kernel approach

Harandi,Mehrtash T., Sanderson, Conrad, Hartley, Richard and Lovell, Brian C. (2012). Sparse coding and dictionary learning for symmetric positive definite matrices: a kernel approach. 12th European Conference on Computer Vision, Florence, Italy, 7-13 October, 2012. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-33709-3_16

Sparse coding and dictionary learning for symmetric positive definite matrices: a kernel approach

2011

Journal Article

Storm‐enhanced plasma density (SED) features, auroral and polar plasma enhancements, and rising topside bubbles of the 31 March 2001 superstorm

Horvath, Ildiko and Lovell, Brian C. (2011). Storm‐enhanced plasma density (SED) features, auroral and polar plasma enhancements, and rising topside bubbles of the 31 March 2001 superstorm. Journal of Geophysical Research - Space Physics, 116 (4) A04307, Article number A04307-n/a. doi: 10.1029/2010JA015514

Storm‐enhanced plasma density (SED) features, auroral and polar plasma enhancements, and rising topside bubbles of the 31 March 2001 superstorm

2011

Journal Article

Face recognition from still images to video sequences: A local-feature-based framework

Chen, Shaokang, Mau, Sandra, Harandi, Mehrtash T., Sanderson, Conrad, Bigdeli, Abbas and Lovell, Brian C. (2011). Face recognition from still images to video sequences: A local-feature-based framework. EURASIP Journal on Image and Video Processing, 2011 (1) 790598, 790598.1-790598.14. doi: 10.1155/2011/790598

Face recognition from still images to video sequences: A local-feature-based framework

2011

Conference Publication

Ensemble of furthest subspace pairs for enhanced image set matching

Harandi, Mehrtash T., Sanderson, Conrad, Bigdeli, Abbas and Lovell, Brian C. (2011). Ensemble of furthest subspace pairs for enhanced image set matching. 18th IEEE International Conference on Image Processing (ICIP), Brussels, Belguim, 11-14 September 2011. Piscataway, NJ, United States: I E E E. doi: 10.1109/ICIP.2011.6116683

Ensemble of furthest subspace pairs for enhanced image set matching

2011

Conference Publication

A face biometric benchmarking review and characterisation

Mau, Sandra, Dadgostar, Farhad, Cullinan, Ian, Bigdeli, Abbas and Lovell, Brian C. (2011). A face biometric benchmarking review and characterisation. IEEE International Conference on Computer Vision Workshops (ICCV Workshops), Barcelona, Spain, 6-13 November 2011. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICCVW.2011.6130510

A face biometric benchmarking review and characterisation

2011

Conference Publication

Dynamic resource aware sensor networks: Integration of sensor cloud and ERPs

Baktashmotlagh, Mahsa, Bigdeli, Abbas and Lovell, Brian C. (2011). Dynamic resource aware sensor networks: Integration of sensor cloud and ERPs. 8th IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS), 2011, Klagenfurt, Austria, 30 August - 2 September 2011. Piscataway, NJ, United States: IEEE. doi: 10.1109/AVSS.2011.6027375

Dynamic resource aware sensor networks: Integration of sensor cloud and ERPs

2011

Conference Publication

Summarisation of surveillance videos by key-frame selection

Yang, Yan, Dadgostar, Farhad, Sanderson, Conrad and Lovell, Brian C. (2011). Summarisation of surveillance videos by key-frame selection. Fifth ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC), Ghent, Belgium, 22-25 August 2011. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICDSC.2011.6042925

Summarisation of surveillance videos by key-frame selection

2011

Conference Publication

MRF-based background initialisation for improved foreground detection in cluttered surveillance videos

Reddy, Vikas, Sanderson, Conrad, Sanin, Andres and Lovell, Brian C. (2011). MRF-based background initialisation for improved foreground detection in cluttered surveillance videos. Asian Conference on Computer Vision, Queenstown, New Zealand, 8-12 November 2010. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-19318-7_43

MRF-based background initialisation for improved foreground detection in cluttered surveillance videos

2011

Conference Publication

Improved anomaly detection in crowded scenes via cell-based analysis of foreground speed, size and texture

Reddy, Vikas, Sanderson, Conrad and Lovell, Brian C. (2011). Improved anomaly detection in crowded scenes via cell-based analysis of foreground speed, size and texture. 2011 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Colorado Springs, CO, United States, 20-25 June 2011. Piscataway, NJ, United States: IEEE. doi: 10.1109/CVPRW.2011.5981799

Improved anomaly detection in crowded scenes via cell-based analysis of foreground speed, size and texture

2011

Conference Publication

Invited paper: Embedded face and biometric technologies for national and border security

Lovell, Brian C., Bigdeli, Abbas and Mau, Sandra (2011). Invited paper: Embedded face and biometric technologies for national and border security. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2011, Colorado Springs, CO, United States, 20-25 June 2011. Piscataway, NJ, United States: IEEE. doi: 10.1109/CVPRW.2011.5981830

Invited paper: Embedded face and biometric technologies for national and border security

2011

Conference Publication

Graph embedding discriminant analysis on Grassmannian manifolds for improved image set matching

Harandi, Mehrtash T., Sanderson, Conrad, Shirazi, Sareh and Lovell, Brian C. (2011). Graph embedding discriminant analysis on Grassmannian manifolds for improved image set matching. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, USA, 20-25 June 2011. Piscataway, NJ, United States: IEEE. doi: 10.1109/CVPR.2011.5995564

Graph embedding discriminant analysis on Grassmannian manifolds for improved image set matching

2011

Conference Publication

An appearance-based approach to assistive identity inference using LBP and colour histograms

Shirazi, Sareh Abolahrari, Dadgostar, Farhad and Lovell, Brian C. (2011). An appearance-based approach to assistive identity inference using LBP and colour histograms. International Workshops on Computer Vision, ACCV 2010, Queenstown, New Zealand, 8-9 November 2010. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-22822-3_24

An appearance-based approach to assistive identity inference using LBP and colour histograms

2011

Conference Publication

An automatic image based single dilution method for end point titre quantitation of antinuclear antibodies tests using HEp-2 cells

Wiliem, Arnold, Hobson, Peter, Minchin, Rodney F. and Lovell, Brian C. (2011). An automatic image based single dilution method for end point titre quantitation of antinuclear antibodies tests using HEp-2 cells. 2011 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2011), Noosa, QLD, Australia, 6 - 8 December 2011. Piscatawa, NJ, United States: IEEE Computer Society. doi: 10.1109/DICTA.2011.9

An automatic image based single dilution method for end point titre quantitation of antinuclear antibodies tests using HEp-2 cells

2011

Journal Article

A low-complexity algorithm for static background estimation from cluttered image sequences in surveillance contexts

Reddy, Vikas, Sanderson, Conrad and Lovell, Brian C. (2011). A low-complexity algorithm for static background estimation from cluttered image sequences in surveillance contexts. EURASIP Journal on Image and Video Processing, 2011 (164956) 164956, 1-14. doi: 10.1155/2011/164956

A low-complexity algorithm for static background estimation from cluttered image sequences in surveillance contexts

2011

Conference Publication

Patch-based probabilistic image quality assessment for face selection and improved video-based face recognition

Wong, Yongkang, Chen, Shaokang, Mau, Sandra, Sanderson, Conrad and Lovell, Brian C. (2011). Patch-based probabilistic image quality assessment for face selection and improved video-based face recognition. 2011 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Colorado Springs, CO, United States, 20-25 June 2011. Piscataway, NJ, United States: IEEE. doi: 10.1109/CVPRW.2011.5981881

Patch-based probabilistic image quality assessment for face selection and improved video-based face recognition

2010

Journal Article

Traveling ionospheric disturbances and their relations to storm-enhanced density features and plasma density irregularities in the local evening and nighttime hours of the Halloween superstorms of 29-31 October 2003

Horvath, I and Lovell, BC (2010). Traveling ionospheric disturbances and their relations to storm-enhanced density features and plasma density irregularities in the local evening and nighttime hours of the Halloween superstorms of 29-31 October 2003. Journal of Geophysical Research A: Space Physics, 115 (9) A09327, A09327-1-A09327-16. doi: 10.1029/2009JA015125

Traveling ionospheric disturbances and their relations to storm-enhanced density features and plasma density irregularities in the local evening and nighttime hours of the Halloween superstorms of 29-31 October 2003

2010

Journal Article

Storm‐enhanced plasma density features investigated during the Bastille Day Superstorm

Horvath, Ildiko and Lovell, Brian C. (2010). Storm‐enhanced plasma density features investigated during the Bastille Day Superstorm. Journal of Geophysical Research - Space Physics, 115 (A06305) A06305, 1-13. doi: 10.1029/2009JA014674

Storm‐enhanced plasma density features investigated during the Bastille Day Superstorm

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

    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

    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

  • Doctor Philosophy

    Generating data-driven continuous optimization problems for benchmarking

    Associate Advisor

    Other advisors: Associate Professor Marcus Gallagher

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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