Mohammed Bennamoun

Winthrop Professor, Ing Ecole Poly. d'Alger, MSc Qu., PhD Qu. & Qld UT

  • The University of Western Australia (M002), 35 Stirling Highway,

    6009 Perth

    Australia

  • 5878 Citations
  • 35 h-Index
20012024
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Personal profile

Biography

Mohammed Bennamoun received his M.Sc. from Queen's University, Kingston, Canada in the area of Control Theory, and his PhD from Queen's /Q.U.T in Brisbane, Australia in the area of Computer Vision. He lectured Robotics at Queen's, and then joined QUT in 1993 as an Associate Lecturer. He then became a Lecturer in 1996 and a Senior Lecturer in 1998 at QUT. He was also the Director of a research Centre from 1998-2002. In Jan. 2003, he joined the Department of Computer Science and Software Engineering at The University of Western Australia (UWA) as an Associate Professor and was promoted to Professor in 2007. He is currently a Winthrop Professor. He served as the Head of the School of Computer Science and Software Engineering at UWA for five years (February 2007-March 2012). He was an Erasmus Mundus Scholar and Visiting Professor in 2006 at the University of Edinburgh. He was also Visiting Professor at CNRS (Centre National de la Recherche Scientifique) and Telecom Lille1, France in 2009, the Helsinki University of Technology in 2006, and the University of Bourgogne and Paris 13 in France in 2002-2003. He is the co-author of the book ``Object Recognition: Fundamentals and Case Studies'', Springer-Verlag, 2001. He won the “Best Supervisor of the Year” Award at QUT. He also received an award for research supervision at UWA in 2008. He published over 120 journal and conference publications. He served as a guest editor for a couple of special issues in International journals, such as the International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI). He was selected to give conference tutorials at the European Conference on Computer Vision (ECCV) and the International Conference on Acoustics Speech and Signal Processing (IEEE ICASSP). He organized several special sessions for conferences; including a special session for the IEEE International Conference in Image Processing (IEEE ICIP). He was on the program committee of many conferences e.g. 3D Digital Imaging and Modeling (3DIM) and the International Conference on Computer Vision. He also contributed in the organisation of many local and international conferences. His areas of interest include control theory, robotics, obstacle avoidance, object recognition, artificial neural networks, signal/image processing and computer vision (particularly 3D).

Research

Computer Vision (particularly 3D), 3D biometrics, 3D object Recognition, Signal/Image Processing, Robotics

Languages

Fluent in Arabic
English and French

Keywords

  • Machine learning / deep learning
  • 3D biometrics
  • 3D reconstruction/recognition
  • Artificial neural networks/deep learning
  • Computer vision
  • Control theory
  • Forensic image processing
  • Pattern recognition
  • Robotics
  • Signal/image processing
  • Virtual reality and immersive environments

Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

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Research Output 2001 2019

3D Shape Analysis: Fundamentals, Theory, and Applications

Laga, H., Guo, Y., Tabia, H., Fisher, R. & Bennamoun, M., 2019, Wiley-Blackwell. 368 p.

Research output: Book/ReportBook

A Fully Automatic Framework for Prediction of 3D Facial Rejuvenation

Shah, S. & Bennamoun, M., 4 Feb 2019, 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ). IEEE, Institute of Electrical and Electronics Engineers, 8634657

Research output: Chapter in Book/Conference paperConference paper

Cosmetics
Learning systems
Fillers

A Training-Free Mesh Upsampling and Morphing Technique for 3D Face Rejuvenation

Shah, S., Bennamoun, M. & Molton, M., 7 Feb 2019, 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ). IEEE, Institute of Electrical and Electronics Engineers, 8634685. (International Conference Image and Vision Computing New Zealand; vol. 2018-November).

Research output: Chapter in Book/Conference paperConference paper

Pixels

Continuous Gesture Segmentation and Recognition using 3DCNN and Convolutional LSTM

Zhu, G., Zhang, L., Shen, P., Song, J., Shah, S. A. A. & Bennamoun, M., Apr 2019, In : IEEE Transactions on Multimedia. p. 1011-1021

Research output: Contribution to journalArticle

Gesture recognition
Neural networks
Hinges
Network architecture
Long short-term memory

Deep learning for scene understanding

Nadeem, U., Shah, S. A. A., Sohel, F., Togneri, R. & Bennamoun, M., 19 Mar 2019, Handbook of deep learning applications. Balas, V. E., Roy, S. S., Sharma, D. & Samui, P. (eds.). Cham: Springer, p. 21-51 27 p. (Smart Innovation, Systems and Technologies; vol. 136).

Research output: Chapter in Book/Conference paperChapter

Computer vision
Neural networks
Network architecture
Hardware
Deep learning

Projects 2003 2024