Professor Brian Lovell

Professor

School of Information Technology and Electrical Engineering
Faculty of Engineering, Architecture and Information Technology
lovell@itee.uq.edu.au
+61 7 336 54134

Overview

Brian C. Lovell was born in Brisbane, Australia in 1960. He received the BE in electrical engineering (Honours I) in 1982, the BSc in computer science in 1983, and the PhD in signal processing in 1991: all from the University of Queensland (UQ). Professor Lovell is Project Leader of the Advanced Surveillance Group at UQ. He served as President of the International Association of Pattern Recognition 2008-2010, and is a Senior Member of the IEEE, Fellow of the IEAust, and voting member for Australia on the Governing Board of the International Association for Pattern Recognition since 1998. Professor Lovell was Program Co-Chair of ICPR2008 in Tampa, Florida, and was General Co-Chair of ACPR2011 in Beijing, General Co-Chair of ICIP2013 in Melbourne, Program Co-Chair of ICPR2016 in Cancun, and Program Co-Chair of ICPR2020 in Milan. The Advanced Surveillance Group has worked with port, rail, and airport organizations as well as several national and international agencies to identify and develop technology-based solutions to address real operational and security concerns.

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

His current research projects are in the fields of:

  • Artificial Intelligence
  • 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 currently recruiting PhD students and Postdoc Fellows in Artificial Intelligence to work with my team. If you are interested and have a strong record from a good university, please send your CV to me. See also my advertised projects.

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

Research Impacts

Apart from papers and grants documented elsewhere, 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 in 2021. 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.

Qualifications

  • Doctor of Philosophy, The University of Queensland
  • Bachelor of Sciences (Computing), The University of Queensland
  • Bach of Engineering (Electrical) Hons 1, The University of Queensland

Publications

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Grants

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Supervision

  • Doctor Philosophy

  • Doctor Philosophy

  • Doctor Philosophy

View all Supervision

Available Projects

  • Neurofibromatosis type 1 (NF1) is one of the most common single-gene inherited disorders globally, with an incidence of 1/2500 individuals. While several phenotypes are associated with the disorder, the most common manifestation is cutaneous neurofibroma. The majority of adults develop these distressing cutaneous tumours (cNF), which increase in severity with age. Adult patients report cosmetic disfigurement due to cNF as the greatest burden of living with NF1. There is no way to predict tumour severity which can range from <100 to thousands. Youth and families experience reduced quality of life due to concerns about this uncertain future. We don’t yet understand why this condition is so variable or have any effective medical treatments. In the proposed research, we will assemble a consortium of internationally recognised experts in NF1 with access and capacity to recruit and phenotype patients to drive the largest genome-wide association and epigenome-wide association studies of the modifier gene networks driving the cutaneous phenotypic variance in NF1. We will then use individualised pharmacological annotation of these networks to identify precision treatment options to mitigate the most distressing and life quality damaging aspects of this devastating illness.

  • Microscopic diagnosis of Gram stain smears is one of the most time and labor intensive tasks in the clinical setting. With the recent development of automated digital pathology scanners, it is now possible to economically obtain high-resolution Gram stain whole slide images for routine diagnosis. This finally opens the doorway to automated identification of bacteria types from digital images in a clinical setting. However, Gram stain whole slide images comprise billions of pixels and suffer from high morphological heterogeneity as well as from many different types of artifacts. Identifying multiple types of tiny bacteria with various densities from an extremely large whole slide image is incredibly challenging. To this end, we propose an end-to-end framework with a novel loss function that tackles the patch aggregation while considering the correlation of different labels in this multi-label scenario. Our framework first effectively integrates the relations among multiple patch features, and then utilizes a class aggregator to generate a robust slide-level feature representation under multi-label setting. Furthermore, we propose a novel loss function integrating two regularization terms: 1) a negative regulator that reduces the confusion between bacteria and negative samples without any bacteria, and 2) an adversarial loss that alleviates the impact of background specification among various tissue samples. We show that the proposed method achieves superior performance compared to several state-of-the-art methods.

  • Incremental learning requires a model to continually learn new tasks from streaming data. However, traditional fine-tuning of a well-trained deep neural network on a new task will dramatically degrade performance on the old task — a problem known as catastrophic forgetting. We address this issue in the context of anchor-free object detection, which is a new trend in computer vision as it is simple, fast, and flexible. Simply adapting current incremental learning strategies fails on these anchor-free detectors due to lack of consideration of their specific model structures. To deal with the challenges of incremental learning on anchor-free object detectors, we propose a novel incremental learning paradigm called Selective and Inter-related Distillation (SID). In addition, a novel evaluation metric is proposed to better assess the performance of detectors under incremental learning conditions. By selective distilling at the proper locations and further transferring additional instance relation knowledge, our method demonstrates significant advantages on the benchmark datasets PASCAL VOC and COCO.

View all Available Projects

Publications

Book

Book Chapter

  • Wu, Lin, Lovell, Brian C. and Wang, Yang (2019). Deep Learning in Person Re-identification for Cyber-Physical Surveillance Systems. Deep Learning Applications for Cyber Security. (pp. 45-72) edited by Alazab, M. and Tang, M. J.. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-13057-2_3

  • Wiliem, Arnold and Lovell, Brian C. (2016). Solving classification problems on human epithelial type 2 cells for anti-nuclear antibodies test: traditional versus contemporary approaches. Pattern Recognition and Big Data. (pp. 605-632) edited by Amita Pal and Sankar K. Pal. New Jersey, United States: World Scientific. doi: 10.1142/9789813144552_0018

  • Harandi, Mehrtash, Basirat, Mina and Lovell, Brian C. (2015). Coordinate coding on the riemannian manifold of symmetric positive-definite matrices for image classification. Riemannian computing in computer vision. (pp. 345-361) edited by Pavan Turaga and Anuj Srivastava. Cham, Switzerland: Springer. doi: 10.1007/978-3-319-22957-7_16

  • 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

  • Shirazi, Sareh, Alavi, Azadeh, Harandi, Mehrtash T. and Lovell, Brian C. (2013). Graph-embedding discriminant analysis on Riemannian manifolds for visual recognition. Graph Embedding for Pattern Analysis. (pp. 157-176) edited by Yun Fu and Yunqian Ma. New York, NY, USA: Springer. doi: 10.1007/978-1-4614-4457-2

  • Harandi, Mehrtash, Taheri, Javid and Lovell, Brian C. (2013). Machine learning applications in computer vision. Image processing: Concepts, methodologies, tools, and applications. (pp. 896-926) edited by Mehdi Khosrow-Pour. Hershey, PA., United States: IGI Global. doi: 10.4018/978-1-4666-3994-2.ch045

  • 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

  • Harandi, Mehrtash, Taheri, Javid and Lovell, Brian C. (2012). Machine learning applications in computer vision. Machine Learning Algorithms for Problem Solving in Computational Applications: Intelligent Techniques. (pp. 99-132) Hershey, Pennsylvania, USA: IGI Global. doi: 10.4018/978-1-4666-1833-6.ch007

  • Lovell, Brian C., Sanderson, Conrad and Shan, Ting (2010). Intelligent surveillance and pose-invariant 2D face classification. Machine interpretation of patterns: Image analysis and data mining. (pp. 207-229) edited by Rajat K. de, Deba Prasad Mandel and Ashish Ghosh. Singapore, Republic of Singapore: World Scientific.

  • 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

  • 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

  • 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.

  • 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.

  • 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

  • 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

  • Shan, T., Lovell, B.C and Chen, S. (2007). Intelligent CCTV via planetary sensor network. Sensor Networks and Configuration : Fundamentals, Standards, Platforms, and Applications. (pp. 463-484) edited by Nitaigour P. Mahalik. Berlin, Germany: Springer.

  • Lovell, Brian C. and Walder, Christian J. (2006). Support Vector Machines for Business Applications. Business Applications and Computational Intelligence. (pp. 267-290) edited by K. Voges and N. Pope. Hershey, PA., U.S.A.: Idea Group. doi: 10.4018/978-1-59140-702-7.ch014

  • Lovell, Brian C. and Caelli, Terry (2005). Hidden Markov models for spatio-temporal pattern recognition. Handbook of pattern recognition and computer vision. (pp. 25-40) edited by C. H. Chen and P. S. P. Wang. Singapore: World Scientific Publications. doi: 10.1142/9789812775320_0002

  • Lovell, Brian C. and Chen, Shaokang (2005). Robust Face Recognition for Data Mining. Encyclopedia of Data Warehousing and Mining. (pp. 965-972) edited by Wang, John. Hershey, USA: Idea Group.

Journal Article

Conference Publication

  • Alhammad, Sarah, Zhao, Kun, Jennings, Anthony, Hobson, Peter, Smith, Daniel F., Baker, Brett, Staweno, Justin and Lovell, Brian C. (2021). Efficient DNN-Based Classification of Whole Slide Gram Stain Images for Microbiology. 2021 Digital Image Computing: Techniques and Applications (DICTA), Gold Coast, QLD Australia, 29 November - 1 December 2021. Piscataway, NJ United States: IEEE. doi: 10.1109/dicta52665.2021.9647415

  • Kurihara, Kohei, Wang, Tianren, Zhang, Teng and Lovell, Brian C. (2021). Boundary guided image translation for pose estimation from ultra-low resolution thermal sensor. 25th International Conference on Pattern Recognition (ICPR), Online, 10-15 January 2021. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICPR48806.2021.9412250

  • Maksoud, Sam, Zhao, Kun, Hobson, Peter, Jennings, Anthony and Lovell, Brian C. (2020). SOS: Selective Objective Switch for Rapid Immunofluorescence Whole Slide Image Classification. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA United States, 13-19 June 2020. Piscataway, NJ United States: IEEE. doi: 10.1109/cvpr42600.2020.00392

  • Maksoud, Sam, Wiliem, Arnold, Zhao, Kun, Zhang, Teng, Wu, Lin and Lovell, Brian (2019). CORAL8: Concurrent object regression for area localization in medical image panels. MICCAI: International Conference on Medical Image Computing and Computer-Assisted Intervention, Shenzhen, China, 13-17 October 2019. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-32239-7_48

  • Wang, Tianren, Zhang, Teng, Liu, Liangchen, Wiliem, Arnold and Lovell, Brian (2019). Cannygan: Edge-Preserving Image Translation with Disentangled Features. 2019 IEEE International Conference on Image Processing (ICIP), Taipei, Taiwan, 22-25 September 2019. Piscataway, NJ United States: IEEE Computer Society. doi: 10.1109/ICIP.2019.8803828

  • Zhao, Kun, Tang, Yu Ji Jerry, Zhang, Teng, Carvajal, Johanna, Smith, Daniel F., Wiliem, Arnold, Hobson, Peter, Jennings, Anthony and Lovell, Brian C. (2019). DGDI: a dataset for detecting glomeruli on renal direct immunofluorescence. 2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2018, Canberra, ACT, Australia, 10-13 December 2018. New York, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/DICTA.2018.8615769

  • Zhang, Teng, Liu, Liangchen, Wiliem, Arnold, Connor, Stephen, Ilich, Zelkjo, Van Der Draai, Eddie and Lovell, Brian (2019). Deep corrosion assessment for electrical transmission towers. 2019 Digital Image Computing: Techniques and Applications, DICTA 2019, Perth, WA, Australia, 2-4 December 2019. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/DICTA47822.2019.8945905

  • Liu, Liangchen, Zhang, Teng, Zhao, Kun, Wiliem, Arnold, Astin-Walmsley, Kieren and Lovell, Brian (2019). Deep inspection: an electrical distribution pole parts study VIA deep neural networks. IEEE International Conference on Image Processing (ICIP), Taipei, Taiwan, 22-25 September 2019. Piscataway, NJ, United States: IEEE Computer Society. doi: 10.1109/ICIP.2019.8803415

  • Li, Meng, Wu, Lin, Wiliem, Arnold, Zhao, Kun, Zhang, Teng and Lovell, Brian (2019). Deep instance-level hard negative mining model for histopathology images. MICCAI: International Conference on Medical Image Computing and Computer-Assisted Intervention, Shenzhen, China, 13-17 October 2019. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-32239-7_57

  • Dianne, Gemma, Wiliem, Arnold and Lovell, Brian C. (2019). Deep-learning from mistakes: automating cloud class refinement for sky image segmentation. 2019 Digital Image Computing: Techniques and Applications, DICTA 2019, Perth, WA, Australia, 2-4 December 2019. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/DICTA47822.2019.8946028

  • San, Wai Y. K., Zhang, Teng, Chen, Shaokang, Wiliem, Arnold, Stefanelli, Dario and Lovell, Brian C. (2019). Early experience of depth estimation on intricate objects using generative adversarial networks. 2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2018, Canberra, ACT, Australia, 10-13 December 2018. New York, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/DICTA.2018.8615783

  • Maksoud, Sam, Wiliem, Arnold and Lovell, Brian (2019). Recurrent attention networks for medical concept prediction. 20th Working Notes of CLEF Conference and Labs of the Evaluation Forum, CLEF 2019, Lugano, Switzerland, 9 - 12 September 2019. Aachen, Germany: CEUR-WS.

  • Peng, Can, Zhao, Kun, Wiliem, Arnold, Zhang, Teng, Hobson, Peter, Jennings, Anthony and Lovell, Brian C. (2019). To what extent does downsampling, compression, and data scarcity impact renal image analysis?. 2019 Digital Image Computing: Techniques and Applications (DICTA), Perth, WA Australia, 2-4 December 2019. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/DICTA47822.2019.8945813

  • Zhang, Teng, Wiliem, Arnold, Hobson, Peter, Jennings, Anthony and Lovell, Brian C. (2019). Training region selector for gram stained slides with limited data: a data distillation approach. 2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2018, Canberra, ACT, 10-13 December 2018. New York, NY, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/DICTA.2018.8615760

  • Darbyshire, R., San, W. Y. K., Plozza, T., Lovell, B. C., Flachowsky, H., Wünsche, J. and Stefanelli, D. (2018). An innovative approach to estimate carbon status for improved crop load management in apple. International Symposium on Flowering, Fruit Set and Alternate Bearing, Palermo, Italy, 19-23 June 2017. Leuven, Belgium: International Society for Horticultural Science. doi: 10.17660/ActaHortic.2018.1229.43

  • Yang, Siqi, Wiliem, Arnold and Lovell, Brian C. (2018). It takes two to tango: cascading off-the-shelf face detectors. IEEE Conference on Computer Vision and Pattern Recognition Workshops in Biometrics (CVPRW), Salt Lake City, UT, United States, 18 - 22 June 2018. Piscataway, NJ, United States: IEEE Computer Society. doi: 10.1109/CVPRW.2018.00095

  • Zhang, Teng, Carvajal, Johanna, Smith, Daniel F., Zhao, Kun, Wiliem, Arnold, Hobson, Peter, Jennings, Anthony and Lovell, Brian C. (2018). SlideNet: fast and accurate slide quality assessment based on deep neural networks. 24th International Conference on Pattern Recognition, ICPR 2018, Beijing, China, 20 - 24 August 2018. Washington, DC, United States: IEEE Computer Society. doi: 10.1109/ICPR.2018.8546205

  • Zhang, Teng, Wiliem, Arnold, Yang, Siqi and Lovell, Brian C. (2018). TV-GAN: generative adversarial network based thermal to visible face recognition. International Conference on Biometrics (ICB), Gold Coast, QLD, Australia, 20 - 23 February 2018. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICB2018.2018.00035

  • Yang, Siqi, Wiliem, Arnold, Chen, Shaokang and Lovell, Brian C. (2018). Using LIP to gloss over faces in single-stage face detection networks. 15th European Conference on Computer Vision, ECCV 2018, Munich, Germany, 8-14 September 2018. Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-01267-0_39

  • Carvajal, Johanna, Smith, Daniel F., Zhao, Kun, Wiliem, Arnold, Finucane, Paul, Hobson, Peter, Jennings, Anthony, McDougall, Rodney and Lovell, Brian (2017). An early experience toward developing computer aided diagnosis for gram-stained smears images. 30th IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Honolulu, HI, United States, 21-26 July 2017. Piscataway, NJ, United States: IEEE. doi: 10.1109/CVPRW.2017.113

  • San, Wai Y. K., Chen, Shaokang, Wiliem, Arnold, Di, Binn and Lovell, Brian C. (2017). How do you develop a face detector for the unconstrained environment?. 2016 International Conference on Image and Vision Computing New Zealand, IVCNZ 2016, Palmerston North, New Zealand, 21 - 22 November 2016. Piscataway, NJ, United States: IEEE Computer Society. doi: 10.1109/IVCNZ.2016.7804414

  • Zhao, Kun, Yang, Siqi, Wiliem, Arnold and Lovell, Brian C. (2017). Landmark manifold: revisiting the Riemannian manifold approach for facial emotion recognition. 2016 23rd International Conference on Pattern Recognition (ICPR), Cancun, Mexico, 4-8 December 2016. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers . doi: 10.1109/ICPR.2016.7899782

  • Yang, Siqi, Wiliem, Arnold and Lovell, Brian C. (2017). The GIST of aligning faces. 2016 23rd International Conference on Pattern Recognition (ICPR), Cancun, Mexico, 4-8 December 2016. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICPR.2016.7900095

  • Yang, Siqi, Wiliem, Arnold and Lovell, Brian C. (2017). To face or not to face: towards reducing false positive of face detection. 2016 International Conference on Image and Vision Computing New Zealand, IVCNZ 2016, Palmerston North, New Zealand, 21 - 22 November 2016. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/IVCNZ.2016.7804415

  • Carvajal, Johanna, Wiliem, Arnold, Sanderson, Conrad and Lovell, Brian (2017). Towards Miss Universe automatic prediction: the evening gown competition. 23rd International Conference on Pattern Recognition, ICPR 2016, Cancun, Mexico, 4 - 8 December 2016. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICPR.2016.7899781

  • Liu, Liangchen, Nie, Feiping, Zhang, Teng, Wiliem, Arnold and Lovell, Brian C. (2017). Unsupervised automatic attribute discovery method via multi-graph clustering. International Conference on Pattern Recognition (ICPR), Cancún, México, 4-8 December 2016. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICPR.2016.7899883

  • Carvajal, Johanna, Wiliem, Arnold, McCool, Chris, Lovell, Brian and Sanderson, Conrad (2016). A Comparative Evaluation of Action Recognition Methods via Riemannian Manifolds, Fisher Vectors and GMMs: Ideal and Challenging Conditions. Pacific-Asia Conference on Knowledge Discovery and Data Mining, Auckland, New Zealand, 19-22 April 2016. CHAM: Springer. doi: 10.1007/978-3-319-42996-0_8

  • Liu, Liangchen, Wiliem, Arnold, Chen, Shaokang and Lovell, Brian C. (2016). Automatic and quantitative evaluation of attribute discovery methods. IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Placid, NY, United States, 7-10 March 2016. Piscataway, NJ, United States: IEEE. doi: 10.1109/WACV.2016.7477693

  • Liu, Liangchen, Wiliem, Arnold, Chen, Shaokang, Zhao, Kun and Lovell, Brian C. (2016). Determining the best attributes for surveillance video keywords generation. 2nd IEEE International Conference on Identity, Security and Behavior Analysis, ISBA 2016, Sendai, Japan, 29 February - 2 March 2016. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ISBA.2016.7477239

  • Lovell, Brian C., Percannella, Gennaro, Saggese, Alessia, Vento, Mario and Wiliem, Arnold (2016). International Contest on Pattern Recognition techniques for indirect immunofluorescence images analysis. 23rd International Conference on Pattern Recognition, ICPR 2016, Cancun, Mexico, December 4, 2016-December 8, 2016. Washington, DC United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICPR.2016.7899610

  • Zhang, Teng, Liu, Liangchen, Wiliem, Arnold and Lovell, Brian (2016). Is Alice chasing or being chased?: Determining subject and object of activities in videos. IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Placid, NY, United States, 7-10 March 2016. Piscataway, NJ, United States: IEEE. doi: 10.1109/WACV.2016.7477710

  • Carvajal, Johanna, McCool, Chris, Lovell, Brian and Sanderson, Conrad (2016). Joint recognition and segmentation of actions via probabilistic integration of spatio-temporal fisher vectors. 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2016 and Workshop on Biologically Inspired Data Mining Techniques, BDM 2016, Workshop on Machine Learning for Sensory Data Analysis, MLSDA 2016, Workshop on Predictive Analytics for Critical Care, PACC 2016 and Workshop on Data Mining in Business and Finance, WDMBF 2016, Auckland,, April 19, 2016-April 19, 2016. Heidelberg, Germany: Springer Verlag. doi: 10.1007/978-3-319-42996-0_10

  • Zhao, Kun, Wiliem, Arnold, Chen, Shaokang and Lovell, Brian C. (2016). Manifold convex hull (MACH): satisfying a need for SPD. 23rd IEEE International Conference on Image Processing, ICIP 2016, Phoenix, AZ, United States, 25-28 September 2016. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICIP.2016.7532357

  • Miros, Anastasia, Wiliem, Arnold, Holohan, Kim, Ball, Lauren, Hobson, Peter and Lovell, Brian C. (2015). A benchmarking platform for mitotic cell classification of ANA IIF HEp-2 images. International Conference on Digital Image Computing: Techniques and Applications, DICTA, Adelaide, SA, Australia, 23-25 November 2015. Piscataway, NJ, United States: IEEE. doi: 10.1109/DICTA.2015.7371213

  • Crossman, Matthew, Wiliem, Arnold, Finucane, Paul, Jennings, Anthony and Lovell, Brian C. (2015). A multiple covariance approach for cell detection of Gram-stained smears images. International Conference on Acoustics, Speech, and Signal Processing (ICASSP) Conference, Brisbane, QLD, Australia, 19-24 April 2015. Piscataway, NJ, United States: IEEE (Institute for Electrical and Electronic Engineers). doi: 10.1109/ICASSP.2015.7178106

  • Samak, Asser, Wiliem, Arnold, Hobson, Peter, Walsh, Michael, Ditchmen, Ted, Troskie, Arne, Barksdale, Sarah, Edwards, Rhonda, Jennings, Anthony and Lovell, Brian C. (2015). An optimization approach to scanning skin direct immunofluorescence specimens. International Conference on Digital Image Computing: Techniques and Applications, DICTA, Adelaide, SA, Australia, 23-25 November 2015. Piscataway, NJ, United States: IEEE. doi: 10.1109/DICTA.2015.7371230

  • Smith, Danny F., Wiliem, Arnold and Lovell, Brian C. (2015). Binary watermarks: a practical method to address face recognition replay attacks on consumer mobile devices. IEEE International Conference on Identity, Security and Behavior Analysis (ISBA), Hong Kong Special Administrative Region of the People's Republic of China, 23-25 March 2015. Piscataway, NJ, United States: IEEE. doi: 10.1109/ISBA.2015.7126344

  • Zhang, Teng, Wiliem, Arnold, Hemson, Graham and Lovell, Brian C. (2015). Detecting kangaroos in the wild: the first step towards automated animal surveillance. International Conference on Acoustics, Speech, and Signal Processing (ICASSP) Conference, Brisbane, QLD, Australia, 19-24 April 2015. Piscataway, NJ, United States: IEEE (Institute for Electrical and Electronic Engineers). doi: 10.1109/ICASSP.2015.7178313

  • Zhao, Kun, Wiliem, Arnold and Lovell, Brian (2015). Kernelised orthonormal random projection on grassmann manifolds with applications to action and gait-based gender recognition. 2015 IEEE International Conference on Identity, Security and Behavior Analysis, ISBA 2015, Hong Kong, March 23-25, 2015. Piscataway, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ISBA.2015.7126348

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • Wiliem, Arnold, Wong, Yongkang, Sanderson, Conrad, Hobson, Peter, Chen, Shaokang and Lovell, Brian C. (2013). Classification of human epithelial type 2 cell indirect immunofluoresence images via codebook based descriptors. 2013 IEEE Workshop on Applications of Computer Vision (WACV), Tampa, FL, United States, 15-17 Janunary 2013. Piscataway, NJ, USA: IEEE (Institute for Electrical and Electronic Engineers). doi: 10.1109/WACV.2013.6475005

  • Harandi, Mehrtash, Sanderson, Conrad, Shen, Chunhua and Lovell, Brian C. (2013). Dictionary earning and sparse coding on Grassmann manifolds: an extrinsic solution. IEEE International Conference on Computer Vision (ICCV), Sydney, Australia, 1-8 December 2013. New York, NY United States: IEEE. doi: 10.1109/ICCV.2013.387

  • 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

  • Baktashmotlagh, Mahsa, Harandi, Mehrtash T., Bigdeli, Abbas, Lovell, Brian C. and Salzmann, Mathieu (2013). Non-linear stationary subspace analysis with application to video classification. 30th International Conference on Machine Learning, Atlanta, GA, United States, 16 - 21 June 2013. Germany: International Machine Learning Society (IMLS).

  • Zhang, Teng, Wiliem, Arnold and Lovell, Brian C. (2013). Region-based anomaly localisation in crowded scenes via trajectory analysis and path prediction. 2013 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2013, Hobart, TAS, Australia, November 26, 2013-November 28, 2013. Piscataway, NJ, United States: IEEE. doi: 10.1109/DICTA.2013.6691519

  • Sanin, Andres, Sanderson, Conrad, Harandi, Mehrtrash and Lovell, Brian (2013). Spatio-temporal covariance descriptors for action and gesture recognition. 2013 IEEE Workshop on Applications of Computer Vision, Tampa, FL, United States, 15-17 January 2013. Piscataway, NJ, United States: IEEE (Institute for Electrical and Electronic Engineers). doi: 10.1109/WACV.2013.6475006

  • Baktashmotlagh, Mahsa, Harandi, Mehrtash T., Lovell, Brian C. and Salzmann, Mathieu (2013). Unsupervised domain adaptation by Domain Invariant Projection. 2013 IEEE International Conference on Computer Vision (ICCV), Sydney, Australia, 1-8 December 2013. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICCV.2013.100

  • Ahmadi, Amin, Bigdeli, Abbas, Baktashmotlagh, Mahsa and Lovell, Brian C. (2012). A wireless mesh sensor network for hazard and safety monitoring at the Port of Brisbane. 37th Annual IEEE Conference on Local Computer Networks (LCN 2012), Clearwater, FL, United States, 22-25 October 2012. Washington, DC, United States: IEEE. doi: 10.1109/LCN.2012.6423601

  • Shirazi, Sareh, Harandi, Mehrtash T., Sanderson, Conrad, Alavi, Azadeh and Lovell, Brian C. (2012). Clustering on Grassmann manifolds via kernel embedding with application to action analysis. 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.2012.6466976

  • Sanderson, Conrad, Harandi, Mehrtash T., Wong, Yongkang and Lovell, Brian C. (2012). Combined learning of salient local descriptors and distance metrics for image set face verification. 9th IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS), Beijing, Peoples R China, 18-21 September 2012. Los Alamitos, CA United States: I E E E Computer Society. doi: 10.1109/AVSS.2012.23

  • Norouznezhad, Ehsan, Harandi, Mehrtash T., Bigdeli, Abbas, Baktash, Mahsa, Postula, Adam and Lovell, Brian C. (2012). Directional space-time oriented gradients for 3D visual pattern analysis. 12th European Conference on Computer Vision, ECCV 2012, Florence, Italy, 7 - 13 October 2012. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-33712-3_53

  • Mau, Sandra, Dadgostar, Farhad and Lovell, Brian C. (2012). Gaussian probabilistic confidence score for biometric applications. 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.2012.6411712

  • 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

  • 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

  • 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

  • Wong, Yongkang, Harandi, Mehrtash T., Sanderson, Conrad and Lovell, Brian C. (2012). On robust biometric identity verification via sparse encoding of faces: Holistic vs local approaches. WCCI 2012 IEEE World Congress on Computational Intelligence, Brisbane Australia, 10-15 June 2012. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/IJCNN.2012.6252611

  • Emami, Ali, Dadgostar, Farhad, Bigdeli, Abbas and Lovell, Brian C. (2012). Role of spatiotemporal oriented energy features for robust visual tracking in video surveillance. 9th IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS), Beijing, Peoples R China, 18-21 September 2012. Los Alamitos, CA United States: I E E E Computer Society. doi: 10.1109/AVSS.2012.64

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • Azman, .Amelia W., Bigdeli, Abbas, Mohd-Mustafah, Yasir, Biglari-Abhari, Morteza and Lovell, Brian C. (2010). A Bayesian network-based framework with Constraint Satisfaction Problem (CSP) formulations for FPGA system design. 21st IEEE International Conference on Application-specific Systems, Architectures and Processors, ASAP 2010, Rennes, France, 7 - 9 July 2010. Washington, DC United States: I E E E Computer Society. doi: 10.1109/ASAP.2010.5540784

  • Dadgostar, Farhad, Bigdeli, Abbas, Mau, Sandra, Smith, Terence and Lovell, Brian (2010). A framework for lab-based real-time video analysis on distributed camera networks. 4th ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2010, Atlanta, GA United States, 31 August - 4 September 2010. New York, NY United States: ACM (Association for Computing Machinery) Press. doi: 10.1145/1865987.1866028

  • Reddy, Vikas, Sanderson, Conrad, Sanin, Andres and Lovell, Brian (2010). Adaptive patch-based background modelling for improved foreground object segmentation and tracking. 2010 7th International Conference on Advanced Video and Signal-Based Surveillance, Boston, MA, United States, 29 August - 1 September 2010. Piscataway, NJ, United States: IEEE Computer Society. doi: 10.1109/AVSS.2010.84

  • Harandi, Mehrtash T., Ahmadabadi, Majid Nili, Araabi, Babak Nadjar, Bigdeli, Abbas and Lovell, Brian C. (2010). Directed random subspace method for face recognition. ICPR 2010: 20th International Conference on Pattern Recognition, Istanbul, Turkey, 23-26 August 2010. Piscataway, NJ, U.S.A.: IEEE - Institute for Electrical and Electronic Engineers. doi: 10.1109/ICPR.2010.659

  • Wong, Yongkang, Sanderson, Conrad, Mau, Sandra and Lovell, Brian C. (2010). Dynamic amelioration of resolution mismatches for local feature based identity inference. 2010 20th International Conference on Pattern Recognition (ICPR 2010), Istanbul, Turkey, 23-26 August 2010. Washington, DC, U.S.A.: IEEE Computer Society. doi: 10.1109/ICPR.2010.299

  • Chen, Shaokang and Lovell, Brian C. (2010). Feature space Hausdorff distance for face recognition. 20th International Conference on Pattern Recognition (ICPR), 2010, Istanbul, Turkey, 23-26 August 2010. Piscataway, NJ, United States: IEEE (Institute for Electrical and Electronic Engineers). doi: 10.1109/ICPR.2010.362

  • Harandi, Mehrtash T., Bigdeli, Abbas and Lovell, Brian C. (2010). Image-set face recognition based on transductive learning. IEEE International Conference on Image Processing, Hong Kong, 26-29 September 2010. Piscataway, NJ, United States: IEEE - Computer Society. doi: 10.1109/ICIP.2010.5651105

  • Sanin, Andres, Sanderson, Conrad and Lovell, Brian (2010). Improved shadow removal for robust person tracking in surveillance scenarios. International Conference on Pattern Recognition (20th, ICPR 2010), Istanbul, Turkey, 23-26 August 2010. Los Alamitos, CA, United States: IEEE. doi: 10.1109/ICPR.2010.43

  • Norouznezhad, Ehsan, Bigdeli, Abbas, Postula, Adam and Lovell, Brian C. (2010). Object tracking on FPGA-based smart cameras using local oriented energy and phase features. International Conference on Distributed Smart Cameras (ICDSC 2010), Atlanta, GA, United States, 31 August - 4 September 2010. New York, United States: ACM. doi: 10.1145/1865987.1865993

  • Reddy, Vikas, Sanderson, Conrad and Lovell, Brian C. (2010). Robust foreground object segmentation via adaptive region-based background modelling. 2010 20th International Conference on Pattern Recognition (ICPR 2010), Istanbul, Turkey, 23-26 August 2010. Washington, DC, U.S.A.: IEEE Computer Society. doi: 10.1109/ICPR.2010.958

  • Bigdeli, Abbas, Postula, Adam, Lovell, Brian C. and Norouznezhad, Ehsan (2010). Robust object tracking using local oriented energy features and its hardware/software implementation. 11th International Conference on Control Automation Robotics & Vision (ICARCV), 2010, Singapore, 7 - 10 December 2010. Piscataway, NJ, United States: IEEE (Institute for Electrical and Electronic Engineers). doi: 10.1109/ICARCV.2010.5707853

  • Mustafah, Yasir M., Bigdeli, Abbas, Azman, Amelia W. and Lovell, Brian C. (2010). Square patch feature based face detection architecture for high resolution smart camera. 4th ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2010, Atlanta, GA United States, 31 August - 4 September 2010. New York, NY United States: ACM (Association for Computing Machinery) Press. doi: 10.1145/1865987.1866015

  • Mustafah, Yasir M., Bigdeli, Abbas, Azman, Amelia W., Dadgostar, Farhad and Lovell, Brian C. (2010). Square patch feature: Faster weak-classifier for robust object detection. 11th International Conference on Control Automation Robotics & Vision (ICARCV), 2010, Singapore, 7-10 December 2010. Piscataway, NJ, United States: IEEE (Institute for Electrical and Electronic Engineers). doi: 10.1109/ICARCV.2010.5707809

  • Mau, Sandra, Chen, Shaokang, Sanderson, Conrad and Lovell, Brian C. (2010). Video face matching using subset selection and clustering of probabilistic multi-region histograms. 25th International Conference of Image and Vision Computing (IVCNZ), Queenstown, New Zealand, 8 - 9 November 2010. Washington, DC, United States: IEEE Computer Society. doi: 10.1109/IVCNZ.2010.6148860

  • Azman, Amelia W, Bigdeli, Abbas, Biglari-Abhari, Morteza, Mustafah, Yasir M. and Lovell B.C. (2009). A BBN-based framework for adaptive IP-reuse. 6th FPGAworld Conference, FPGAworld 2009, Stockholm, Sweden, 10 September 2009. New York , NY United States: ACM (Association for Computing Machinery) Press. doi: 10.1145/1667520.1667521

  • Singh, A., Sawan, S., Hanmandlu, M., Madasu, V. K. and Lovell, B. C. (2009). An abandoned object detection system based on dual background segmentation. AVSS 2009: 6th IEEE International Conference on Advanced Video and Signal Based Surveillance, Genoa, Italy, 2-4 September 2009. Los Alamitos, CA, U.S.A.: Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/AVSS.2009.74

  • Reddy, Vikas, Sanderson, Conrad and Lovell, Brian, C. (2009). An efficient and robust sequential algorithm for background estimation in video surveillance. International Conference on Image Processing (ICIP 2009), Cairo, Egypt, 7-12 November 2009. Piscataway NJ, United States: IEEE. doi: 10.1109/ICIP.2009.5413450

  • Reddy, Vikas, Sanderson, Conrad, Lovell, Brian, C. and Bigdeli, Abbas (2009). An efficient background estimation algorithm for embedded smart cameras. 3rd ACM/IEEE International Conference on Distributed Smart Cameras, Como, Italy, 30 August 2009 - 2 September 2009. Piscataway NJ, USA: IEEE. doi: 10.1109/ICDSC.2009.5289348

  • Kumar, A., Hanmandlu, M., Madasu, V. K. and Lovell, B. C. (2009). Biometric Authentication Based on Infrared Thermal Hand Vein Patterns. Digital Image Computing: Techniques and Applications, 2009. DICTA '09, Melbourne, Victoria, Australia, 1-3 December, 2009. Los Alamitos, California: IEEE. doi: 10.1109/DICTA.2009.63

  • Madasu, Vamsi K. and Lovell, Brian C. (2009). Blotch detection in pigmented skin lesions using fuzzy co-clustering and texture segmentation. DICTA 2009, Melbourne , Australia, 1-3 December 2009. New Jersey, U.S.A.: CPS Publishing Services. doi: 10.1109/DICTA.2009.15

  • Yang, Yan, Lovell, Brian C. and Dadgostar, Farhad (2009). Content-Based Video Retrieval (CBVR) system for CCTV surveillance videos. 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.2009.36

  • Susan, Seba, Hanmandlu, M., Madasu, Vamsi K. and Lovell, Brian C. (2009). Detection of skin lesions by fuzzy entropy based texel identification. ISPA 2009, Salzburg, Austria, 16-18 September 2009. Salzburg, Austria: University of Salzburg.

  • 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

  • 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, ICDSC 2009, Como, Italy, 30 August - 2 September 2009. Piscataway, NJ United States: I E E E. doi: 10.1109/ICDSC.2009.5289346

  • 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.

  • Sanderson, Conrad and Lovell, Brian C. (2009). Multi-region probabilistic histograms for robust and scalable identity inference. 3rd IAPR/IEEE International Conference on Biometrics, Alghero, Italy, 2-5 June 2009. Berlin / Heidelberg: Springer Verlag. doi: 10.1007/978-3-642-01793-3_21

  • Wong, Yong, Sanderson, Conrad and Lovell, Brian C. (2009). Regression based non-frontal face synthesis for improved identity verification. 13th International Conference, CAIP 2009, Munster, Germany, 2-4 September, 2009. Heidelberg, Germany: Springer-Verlag. doi: 10.1007/978-3-642-03767-2_14

  • Chen, Shaokang, Sanderson, Conrad, Sun, Sai and Lovell, Brian (2009). Representative feature chain for single gallery image face recognition. 19th International Conference on Pattern Recognition, Tampa, Florida, USA, 8-11 December, 2008. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICPR.2008.4760975

  • Smith, Andrew W. B. and Lovell, Brian C. (2009). Self occlusions and graph based edge measurement schemes for visual tracking applications. 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.2009.74

  • Kong, Suyu, Bhuyan, M. K., Sanderson, C. and Lovell, Brian C. (2009). Tracking of persons for video surveillance of unattended environments. ICPR 2008: 19th International Conference on Pattern Recognition, Tampa, FL, USA, 8-11 December, 2008. Washington, DC, United States: I E E E Computer Society. doi: 10.1109/ICPR.2008.4761338

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • Mustafah, Y. M., Azman, A., Bigdeli, A. and Lovell, B. C. (2007). An automated face recognition system for intelligence surveillance: Smart camera recognizing faces in the crowd. First ACM/IEEE International Conference on Distributed Smart Cameras 2007, Vienna, Austria, 25-28 September 2007. Piscataway, NJ, U.S.A.: IEEE - Institute of Electrical Electronics Engineers Inc.. doi: 10.1109/ICDSC.2007.4357518

  • Kong, Suyu, Sanderson, C. and Lovell, Brian C. (2007). Classifying and tracking multiple persons for proactive surveillance of mass transport systems. IEEE Conference on Advanced Video and Signal Based Surveillance 2007 (AVSS2007), London, UK, 5-7 September 2007. Piscataway, NJ, USA: IEEE. doi: 10.1109/AVSS.2007.4425303

  • Chen S., Shan T. and Lovell B.C. (2007). Combining classifiers in rotated face space. Australian Pattern Recognition Society (APRS), Glenelg, SA, December 3, 2007-December 5, 2007. IEEE. doi: 10.1109/DICTA.2007.4426822

  • 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

  • Azman, A. W., Bigdeli, A., Mustafah, Y. M. and Lovell, B. C. (2007). Optimizing resources of an FPGA-based smart camera architecture. 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.2007.4426853

  • 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

  • Chen, S., Shan, T. and Lovell, B. C. (2007). Robust Face Recognition in Rotated Eigen Space. The Twenty-second International Image and Vision Computing New Zealand Conference, Hamilton, N.Z, 5-7th December.

  • 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.

  • Conrad Sanderson, Ting Shan and Brian C. Lovell (2007). Towards Pose-Invariant 2D Face Classification for Surveillance. Analysis and Modeling of Faces and Gestures Third InternationalWorkshop (AMFG 2007), Rio de Janeiro, Brazil, 20 October 2007. Heidelberg, Germany: Springer. doi: 10.1007/978-3-540-75690-3_21

  • Shan, Ting, Chen, Shaokang, Sanderson, Conrad and Lovell, Brian C. (2007). Towards robust face recognition for intelligent-CCTV based surveillance using one gallery image. IEEE Conference on Advanced Video and Signal Based Surveillance, 2007 (AVSS 2007), London, United Kingdom, 5-7 September 2007. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICICIC.2007.377

  • Bigdeli A., Lovell B. C., Sanderson C., Shan, T. and Chen S. (2007). Vision Processing in Intelligent CCTV for Mass Transport Security. SAFE 2007: Workshop on Signal Processing Applications for Public Security and Forensics, Washington, DC, USA,, 11-13 April 2007. Washington, DC, USA,: IEEE Signal Processing Society.

  • Shan, Ting, Lovell, Brian C. and Chen, Shaokang (2006). Face recognition robust to head pose from one sample image. 18th International Conference on Pattern Recogntion (ICPR 2006), Hong Kong, 20-24 August 2006. Washington, DC, United States: IEEE. doi: 10.1109/ICPR.2006.527

  • Smith, A. W. B. and Lovell, B. C. (2006). Measurement Function Design for Visual Tracking Applications. 18th International Conference on Pattern Recognition (ICPR 2006), Hong Kong, 20-24 August, 2006. U.S.A.: IEEE. doi: 10.1109/ICPR.2006.785

  • Wilson, Simon, Lovell, Brian, Anne, Chang and Masters, Brent (2005). Real-time quantitative bronchoscopy. Digital Imaging Computing: Techniques and Applications, DICTA 2005, , , December 6, 2005-December 8, 2005. doi: 10.1109/DICTA.2005.1578149

  • McKinnon, D. N. R. and Lovell, B. C. (2005). A Study of the Optimality of Approximate Maximum Likelihood Estimation. APRS Workshop on Digital Image Computing (WFIC 2005), Brisbane, Australia, 21 February, 2005. Brisbane, Australia: The University of Queensland.

  • Chiranjivi, G. V. S., Madasu, Vamsi Krishna, Hanmandlu, Madasu and Lovell, Brian C. (2005). Arrhythmia detection in human electrocardiogram. APRS Workshop on Digital Image Computing, Brisbane, 21 February, 2005. Brisbane, Australia: The University of Queensland.

  • Madasu, Vamsi K., Lovell, Brian C. and Kubik, Kurt (2005). Automatic Handwritten Signature Verification System for Australian Passports. Science, Engineering and Technology Summit on Counter-Terrorism Technology, Canberra, 14 July, 2005.

  • Madasu, Vamsi K. and Lovell, Brian C. (2005). Automatic Segmentation and Recognition of Bank Cheque Fields. Digital Image Computing: Techniques and Applications (DICTA 20005), Cairns, 6-8 December, 2005. Los Altimos, CA: IEEE CS Press. doi: 10.1109/DICTA.2005.1578131

  • Chen, Shaokang, Lovell, Brian C. and Shan, Ting (2005). Combining Generative and Discriminative Learning for Face Recognition. Digital Image Computing: Techniques and Applications (DICTA 2005), Cairns, 6-8 December, 2005. Los Alamitos, CA, USA: IEEE CS Press. doi: 10.1109/DICTA.2005.1578103

  • Lovell, Brian C. (2005). Globally optimal 3D image reconstruction and segmentation via energy minimisation techniques. 1st International Conference on Pattern Recognition and Machine Intelligence (PReMI2005), Kolkata, India, 18-22 December 2005. Berlin, Germany: Springer. doi: 10.1007/11590316_16

  • Madasu, Vamsi K., Lovell, Brian C. and Hanmandlu, Madasu (2005). Hand Printed Character Recognition Using Neural Networks. International Conference on Cognition and Recognition, Mysore, India, 22-23 December, 2005.

  • Liu, Nianjun and Lovell, Brian C. (2005). Hand gesture extraction by active shape models. Digital Image Computing: Techniques and Applications (DICTA 2005), Cairns, Australia, 6-8 December, 2005. Los Alamitos, CA, USA: IEEE CS Press. doi: 10.1109/DICTA.2005.1578108

  • Walder, C. J. and Lovell, B. C. (2005). Homogenised Virtual Support Vector Machines. Digital Image Computing: Techniques and Applications (DICTA 2005), Cairns, Australia, 6-8 December, 2005. Los Alamitos, CA, USA: IEEE CS Press. doi: 10.1109/DICTA.2005.1578155

  • McKinnon, David N. R. and Lovell, Brian C. (2005). Manufacturing Multiple View Constraints. APRS Workshop on Digital Image Computing, Brisbane, 21 February, 2005. Brisbane: The Australian Pattern Recognition Society.

  • Seitner, Florian H. and Lovell, Brian C. (2005). Pedestrian Tracking Based on Colour and Spatial Information. Digital Image Computing: Techniques and Applications (DICTA 2005), Cairns, Australia, 6-8 December, 2005. Los Alamitos, CA: IEEE CS Press. doi: 10.1109/DICTA.2005.1578105

  • Shan, Ting, Lovell, Brian C. and Chen, Shaokang (2005). Person Location Service on the Planetary Sensor Network. APRS Workshop on Digital Image Computing, Brisbane, 21 February, 2005. Brisbane, Austrlaia: The Australian Pattern Recognition Society.

  • Wilson, Simon, Lovell, Brian C., Chang, Anne and Masters, Brent (2005). Real-Time Quantitative Bronchoscopy. Digital Image Computing: Techniques and Applications (DICTA 2005), Cairns, Australia, 6-8 December, 2005. Los Alamitos, CA.: IEEE CS Press.

  • Lovell, Brian C. and Chen, Shaokang (2005). Robust face recognition for data mining. APRS Workshop on Digital Image Computing, Brisbane, Australia, 21st February, 2005. St Lucia, Australia: The University of Queensland.

  • Wilson, S., Lovell, B. C., Chang, A. and Masters, B. (2005). Visual Odometry for Quantitative Bronchoscopy Using Optical Flow. APRS Workshop on Digital Image Computing 2005, Brisbane, Australia, 21 February, 2005. Birsbane, Australia: University of Queensland.

  • Smith, Andrew W. B. and Lovell, Brian C. (2005). Visual tracking for sports applications. APRS Workshop on Digital Image Computing, Brisbane, 21 February, 2005. St Lucia, Australia: The University of Queensland.

  • Leung, C. W., Appleton, B. C., Lovell, B. C. and Sun, C. (2004). An Energy Minimisation Approach to Stereo-Temporal Dense Reconstruction. International Conference on Pattern Recognition, Cambridge, United Kingdom, 23-26 August. Los Alamitos, California: IEEE Computer Society. doi: 10.1109/ICPR.2004.1333708

  • Rottensteiner, F., Trinder, J., Clode, S., Kubik, K. and Lovell, B. C. (2004). Building Detection by Dempster-Shafer Fusion of LIDAR Data and Multispectral Aerial Imagery. International Conference on Pattern Recognition, Cambridge, UK, 23-26 August. Los Alamitos, California: The Institute of Electrical and Electronics Engineers Computer Society. doi: 10.1109/ICPR.2004.1334203

  • Liu, Nianjun, Davis, Richard I. A., Lovell, Brian C. and Kootsookos, Peter J. (2004). Effect of Initial HMM Choices in Multiple Sequence Training for Gesture Recognition. International Conference on Information Technology (ITCC 2004), Las Vegas, Nevada, U.S.A., 5-7 April, 2004. Los Alamitos, California: The Institute of Electrical and Electronics Engineers Computer Society. doi: 10.1109/ITCC.2004.1286531

  • Chen, Shaokang and Lovell, Brian C. (2004). Illumination and Expression Invariant Face Recognition With One Sample Image. The Seventeenth International Conference on Pattern Recognition, Cambridge, UK, 23-26 August, 2004. Los Alamitos, California: The Institute of Electrical and Electronics Engineers Computer Society. doi: 10.1109/ICPR.2004.1334112

  • Liu, N., Lovell, B. C., Kootsookos, P. J. and Davis, R. I. (2004). Model Structure Selection and Training Algorithms for a HMM Gesture Recognition System. International Workshop in Frontiers of Handwriting Recognition, Tokyo, 26-29 October. Los Alamitos, California: The Institute of Electrical and Electronics Engineers Computer Society.

  • McKinnon, David N. and Lovell, B. C. (2004). Tensor Algebra: A Combinatorial Approach to the Projective Geometry of Figures. IWCIA - Tenth International Workshop on Combinatorial Image Analysis, Auckland, New Zealand, 1-3 December, 2004. Berlin: Springer. doi: 10.1007/b103936

  • Liu, N., Lovell, B. C., Kootsookos, P. J. and Davis, R. I. A. (2004). Understanding HMM Training For Video Gesture Recognition. The Analog and Digital Techniques in Electrical Engineering, Chiang Mai, Thailand, 21-24 November, 2004. Piscataway, NJ: The Institute of Electrical and Electronics Engineers.

  • Leung, Carlos and Lovell, Brian C. (2003). 3D Reconstruction through Segmentation of Multi-View Image Sequences. Workshop on Digital Image Computing, Brisbane, 7 February, 2003. Brisbane: Australian Pattern Recognition Society.

  • McKinnon, David, Jones, Barry and Lovell, Brian C. (2003). A Closed Form Solution to the Reconstruction and Multi-View Constraints of the Degree d Apparent Contour. Workshop on Digital Image Computing, Brisbane, 7 February, 2003.

  • 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.

  • Lovell, Brian C. (2003). Academic Performance of International Students in Electrical Engineering at the University of Queensland. Australian Association for Engineering Education Conference, Melbourne, 29 September - 4 October. Melbourne: Australian Association for Engineering Education.

  • Walder, Christian, Lovell, Brian C. and Kootsookos, Peter J. (2003). Algebraic Curve Fitting Support Vector Machines. Digital Image Computing Techniques and Applications 2003, Sydney, December, 2003. Sydney: CSIRO.

  • 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.

  • Smith, Andrew W. B. and Lovell, Brian C. (2003). Autonomous Sports Training from Visual Cues. The 8th Australian and New Zealand Intelligent Information Systems Conference, Sydney, 10-12 December, 2003. Brisbane: Queensland University of Technology.

  • Andrews, Robert J. and Lovell, Brian C. (2003). Color Optical Flow. Workshop on Digital Image Computing, Brisbane, 7 February, 2003. Brisbane: Australian Pattern Recognition Society.

  • Liu, Nianjun, Lovell, Brian C. and Kootsookos, Peter J. (2003). Evaluation of HMM training algorithms for letter hand gesture recognition. IEEE International Symposium on Signal Processing and Information Technology, Darmstadt, Germany, 14-17 December. Darmstadt, Germany: The Institute of Electrical and Electronics Engineers. doi: 10.1109/ISSPIT.2003.1341204

  • 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.

  • Liu, Nianjun and Lovell, Brian C. (2003). Gesture Classification Using Hidden Markov Models and Viterbi Path Counting. The Seventh Biennial Australian Pattern Recognition Society Conference, Sydney, 10-12 December. Sydney: CSIRO.

  • Lovell, Brian C. (2003). Hidden Markov Models for Spatio-Temporal Pattern Recognition and Image Segmentation. International Conference on Advances in Pattern Recognition, Calcutta, 10-13 December. Kolkata: Allied Publishers.

  • Davis, Richard I. A. and Lovell, Brian C. (2003). Improved Ensemble Training for Hidden Markov Models using Random Relative Node Permutations. The 2003 APRS Workshop on Digital Image Computing, Brisbane, 7 February, 2003. Brisbane: Australian Pattern Recognition Society.

  • 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.

  • 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.

  • 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.

  • McKinnon, David N. and Lovell, Brian C. (2003). Towards Closed Form Solutions to the Multiview Constraints of Curves and Surfaces. The Seventh Biennial Australian Pattern Recognition Society Conference, Sydney, 10- 12 December. Sydney: CSIRO.

  • Walder, Christian J., Kootsookos, Peter J. and Lovell, Brian C. (2003). Towards a Maximum Entropy Method for Estimating HMM Parameters. Workshop on Digital Image Computing, Brisbane, February 7, 2003. Brisbane: Australian Pattern Recognition Society.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

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

  • 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.

  • 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.

  • 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.

  • 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.

  • Liu, Nianjun and Lovell, Brian C. (2001). MMX-Accelerated Real-Time Hand Tracking System. IVCNZ 2001, Dunedin, New Zealand, 26-28 November, 2001.

  • Liu, N. and Lovell, B. C. (2001). MMX-accelerated real-time hand tracking system. Image and Vision Computing 2001, Dunedin, New Zealand, 26-28 November, 2001. Dunedin, New Zealand: Wickliffe Limited.

  • 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.

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

  • 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.

  • Heckenberg, D. and Lovell, Brian C. (2000). MIME: A Gesture-Driven Computer Interface. Visual Communications and Image Processing, SPIE, V 4067, Perth, Australia, 20-23 June, 2000. doi: 10.1117/12.386641

  • Cendrillon, Raphael and Lovell, Brian C. (2000). Real-Time Face Recognition Using Eigenfaces. Visual Communications and Image Processing, SPIE, V 4067, Perth, 20-23 June, 2000. doi: 10.1117/12.386642

  • Bamford, Pascal and Lovell, Brian C. (1999). A methodology for quality control in cell nucleus segmentation. Digital Image Computing: Techniques and Applications, Perth, Australia, 7th - 8th December, 1999. Perth: Australian Pattern Recognition Society.

  • Lovell, Brian C., Kootsookos, Peter J. and Longstaff, Dennis (1999). On the Open-Ended Classifier Problem in the Context of Human Face Recognition and Tracking in Cluttered Visual Environments. Digital Image Computing Techniques and Applications, Perth, 7th - 8th December, 1999. Perth: Australian Pattern Recognition Society.

  • Bamford, P. C., Jackway, P. T. and Lovell, Brian (1999). Progress in the robust automated segmentation of real cell images. New Approaches in Medical Image Analysis, Ballarat, Australia, 31 July 1998. Bellingham: SPIE - The Int. Society for Optical Engineering. doi: 10.1117/12.351626

  • Bamford, Pascal and Lovell, Brian C. (1998). Bayesian Analysis of Cell Nucleus Segmentation by a Viterbi Search Based Active Contour. International Conference on Pattern Recognition, Brisbane, Australia, August 16 - 20, 1998.

  • Bamford, Pascal and Lovell, Brian C. (1998). Improving the Robustness of Cell Nucleus Segmentation. British Machine Vision Conference, Southampton, UK, September 14 - 17, 1998.

  • Paget, R., Lovell, Brian C. and Longstaff, I. D. (1997). Texture Classification Using Nonparametric Random Fields. 13th International Conference on Signal Processing, Santorini, Greece, July 2-4, 1997.

  • Bamford Pascal and Lovell Brian (1997). Two-stage scene segmentation scheme for the automatic collection of cervical cell images. Proceedings of the 1997 IEEE TENCON Conference. Part 1 (of 2), Brisbane, Australia, December 2, 1997-December 4, 1997.

  • Bamford, Pascal and Lovell, Brian C. (1996). A Water Immersion Algorithm for Cytological Image Segmentation. APRS Image Segmentation Workshop, Sydney, Australia, 13 December, 1996.

  • Bradley, Andrew P., Jackway, Paul and Lovell, Brian C. (1995). Classification In Scale-Space: Applications To Texture. XIVth International Conference on Information Processing in Medical Imaging (IPMI), Ile de Berder, France,

  • Bradley, AP, Jackway, PT and Lovell, BC (1995). Classification in scale-space: Applications to texture analysis. 14th International Conference on Information Processing in Medical Imaging, Ile De Berder France, Jun, 1995. DORDRECHT: KLUWER ACADEMIC PUBL.

  • Bradley, Andrew P. and Lovell, Brian C. (1995). Cost-Sensitive Decision Tree Pruning: Use of the ROC Curve. Eighth Australian Joint Conference on Artificial Intelligence, Canberra, Australia, November, 1995.

  • Bradley, Andrew P., Lovell, Brian C. and Jackway, Paul T. (1995). Scale-Space Texture Analysis. Digital Image Computing: Techniques and Applications (DICTA '95), Brisbane, December, 1995.

  • Jeacocke, Mark B. and Lovell, Brian C. (1994). A Multi-Resolution Algorithm for Cytological Image Segmentation. Australian and New Zealand Conference on Intelligent Information Systems, Brisbane, Australia, 1994.

  • Walker, Ross F., Jackway, Paul, Lovell, Brian C. and Longstaff, I. D. (1994). Classification Of Cervical Cell Nuclei Using Morphological Segmentation And Texture Feature Extraction. Australian and New Zealand Conference on Intelligent Information Systems, Brisbane, Australia, 1994.

  • Bradley, Andrew P. and Lovell, Brian C. (1994). Inductive Learning using Multiscale Classification. Fifth Australian Conference on Neural Networks (ACNN '94), Brisbane, Australia, February, 1994.

  • Lee, S. and Lovell, Brian C. (1994). Modelling and Classification of Shapes in Two-Dimensions Using Vector Quantization. IEEE International Conference on ASSP, Adelaide Australia, 1994.

  • Bradley, Andrew P., Lovell, Brian C., Ray, Michael and Hawson, Geoffrey (1994). On the Methodology for Comparing Learning Algorithms: A Case Study. Australian and New Zealand Conference on Intelligent Information Systems (ANZIIS'94), Brisbane, Australia, November, 1994.

  • Paget, R., Lovell, Brian C. and Longstaff, I. D. (1993). Mutiprocessor Adaptation of a Texture Segmentation Scheme for Satellite Radar Images. Digital Image Computing: Techniques and Applications, Sydney, Australia, December, 1993.

  • Kootsookos, Peter J., Tsoi, A. C. and Lovell, Brian C. (1992). Speech Enhancement for Robust Speaker Verification. Speech, Science and Technology conference, Brisbane, December.

  • Lovell, Brian C., Kootsookos, Peter J. and Williamson, R. C. (1991). The Circular Nature Of Discrete-Time Frequency Estimates. IEEE International Conference on ASSP, Toronto, May, 1991. Publ by IEEE.

  • Lovell, Brian C., Kootsookos, Peter J. and Williamson, Robert C. (1990). Efficient Frequency Estimation and Time-Frequency Representations. International Symposium on Signal Processing and Its Applications 1990, Gold Coast, Australia, August.

  • Boashash, Boualem, Lovell, Brian C. and Kootsookos, Peter J. (1989). Time-Frequency Signal Analysis and Instantaneous Frequency Estimation: Methodology, Relationships and Implementation. International Symposium on Circuits and Systems, 1989.

  • Boashash, B. and Lovell, Brian C. (1988). Segmentation of Non-Stationary Signals with Applications. IEEE International Conference on ASSP, New York, 1988.

Edited Outputs

  • B. C. Lovell, A. J. Maeder, T. Caelli and S. Ourselin eds. (2005). Digital Image Computing: Techniques and Applications (DICTA 2005). Digital Imaging Computing: Techniques and Applications (DICTA 2005), Cairns, QLD Australia, 6-8 December 2005. Los Alamitos, CA United States: IEEE Computer Society.

  • Lovell, Brian C., Maeder, Anthony J., Caelli, Terry and Ourselin, Sebastien eds. (2005). Digital image computing: Techniques and applications. DICTA 2005: Digital Image Computing Techniques and Applications, Cairns, Qld., Australia, 6-8 December, 2005. Los Alamitos, Calif.: IEEE.

  • Brian C. Lovell and Anthony J. Maeder eds. (2005). Proceedings of the APRS Workshop on Digital Image Computing. APRS Workshop on Digital Image Computing, Griffith University, Southbank, Brisbane, Australia, 21 February, 2005. St Lucia, Queensland: The University of Queensland.

  • Lovell, Brian C. and Maeder, Anthony J. eds. (2003). Proceedings of the 2003 APRS Workshop on Digital Image Computing. Workshop on Digital Image Computing, Brisbane, February 7, 2003.

  • 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.

  • Brian C. Lovell, Duncan A. Campbell, Clinton B. Fookes and Anthony J. Maeder eds. (2003). Proceedings of the Eighth Australian and New Zealand Intelligent Information Systems Conference. Proceedings of the Eighth Australian and New Zealand Intelligent Information Systems Conference (ANZIIS 2003), Sydney, Australia, 10-12 December, 2003. Brisbane, QLD: The Australian Pattern Recognition Society.

Other Outputs

Grants (Administered at UQ)

PhD and MPhil Supervision

Current Supervision

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Principal Advisor

    Other advisors:

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Principal Advisor

  • Master Philosophy — Associate Advisor

  • Doctor Philosophy — Associate Advisor

  • Master Philosophy — Associate Advisor

    Other advisors:

Completed Supervision

Possible Research Projects

Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.

  • Neurofibromatosis type 1 (NF1) is one of the most common single-gene inherited disorders globally, with an incidence of 1/2500 individuals. While several phenotypes are associated with the disorder, the most common manifestation is cutaneous neurofibroma. The majority of adults develop these distressing cutaneous tumours (cNF), which increase in severity with age. Adult patients report cosmetic disfigurement due to cNF as the greatest burden of living with NF1. There is no way to predict tumour severity which can range from <100 to thousands. Youth and families experience reduced quality of life due to concerns about this uncertain future. We don’t yet understand why this condition is so variable or have any effective medical treatments. In the proposed research, we will assemble a consortium of internationally recognised experts in NF1 with access and capacity to recruit and phenotype patients to drive the largest genome-wide association and epigenome-wide association studies of the modifier gene networks driving the cutaneous phenotypic variance in NF1. We will then use individualised pharmacological annotation of these networks to identify precision treatment options to mitigate the most distressing and life quality damaging aspects of this devastating illness.

  • Microscopic diagnosis of Gram stain smears is one of the most time and labor intensive tasks in the clinical setting. With the recent development of automated digital pathology scanners, it is now possible to economically obtain high-resolution Gram stain whole slide images for routine diagnosis. This finally opens the doorway to automated identification of bacteria types from digital images in a clinical setting. However, Gram stain whole slide images comprise billions of pixels and suffer from high morphological heterogeneity as well as from many different types of artifacts. Identifying multiple types of tiny bacteria with various densities from an extremely large whole slide image is incredibly challenging. To this end, we propose an end-to-end framework with a novel loss function that tackles the patch aggregation while considering the correlation of different labels in this multi-label scenario. Our framework first effectively integrates the relations among multiple patch features, and then utilizes a class aggregator to generate a robust slide-level feature representation under multi-label setting. Furthermore, we propose a novel loss function integrating two regularization terms: 1) a negative regulator that reduces the confusion between bacteria and negative samples without any bacteria, and 2) an adversarial loss that alleviates the impact of background specification among various tissue samples. We show that the proposed method achieves superior performance compared to several state-of-the-art methods.

  • Incremental learning requires a model to continually learn new tasks from streaming data. However, traditional fine-tuning of a well-trained deep neural network on a new task will dramatically degrade performance on the old task — a problem known as catastrophic forgetting. We address this issue in the context of anchor-free object detection, which is a new trend in computer vision as it is simple, fast, and flexible. Simply adapting current incremental learning strategies fails on these anchor-free detectors due to lack of consideration of their specific model structures. To deal with the challenges of incremental learning on anchor-free object detectors, we propose a novel incremental learning paradigm called Selective and Inter-related Distillation (SID). In addition, a novel evaluation metric is proposed to better assess the performance of detectors under incremental learning conditions. By selective distilling at the proper locations and further transferring additional instance relation knowledge, our method demonstrates significant advantages on the benchmark datasets PASCAL VOC and COCO.

  • Text-to-Face (TTF) synthesis is a challenging task with great potential for diverse computer vision applications. Compared to Text-to-Image (TTI) synthesis tasks, the textual description of faces can be much more complicated and detailed due to the variety of facial attributes and the parsing of high dimensional abstract natural language. We propose a text-to-face model that should not only produce images in high resolution (10241024) and text-to-image consistency, but also output multiple faces to cover a wide range of unspecified facial features in a natural way. By fine-tuning the multi-label classifier and image encoder, our model obtains the vectors and image embeddings which are used to manipulate the noise vector sampled from the normal distribution. Afterwards, the manipulated noise vector is fed into a pre-trained high-resolution image generator to produce a set of faces with desired facial attributes. We refer to our model as TTF-HD. Experimental results show that TTF-HD generates high-quality faces and achieves state-of-the-art performance.