Dr Kam Wong
Senior Lecturer In Computing & Communications
School of Computing & Communications
Biography
Professional biography
Dr. Patrick Wong joined the Open University in December 1999 and is a senior lecturer at the School of Computing and Communications. Since 2023, he has been a Deputy Head of School and help managing the school. He is chairing the Next Generation Multimedia Research Group and has supervised 6 PhD students to completion.
He is a member of the Institution of Engineering and Technology (IET) and a chartered engineer. Between 2015 to 2018, he was an executive committee member of the IET's Vision and Imaging Professional network.
He is a member of the Editorial board of Emerald's Kybernetes (The international journal of cybernetics, systems and management sciences), and is the guest editor of the special issue of Object Detection and Image Classification in the MDPI Applied Sciences journal. He also regularly reviews paper for a number of journals which includes IET Communications, IET Image Processing, Elsevier's Physics Letters A, Physica and the MDPI Applied Sciences journal.
His main sport is table tennis. In fact, he chairs the Open University Table Tennis Club and also plays league matches at Milton Keynes Table Tennis League.
Research interests
His research interests are in artificial intelligent applications, especially in computer vision applications, biometrics recognition, deepfake detection, image processing and fault prediction and detection. He has been supervising PhD students on projects related to Multiview Image Processing and Cognitive Radio Technologies. He is also developing an automatic table tennis umpiring system using image/video processing and artificial intelligent techniques. He was a runners up of the BCS Competition for the Machine Intelligence Prize, which was held at ES2002 in Cambridge on 11th December 2002.
External Examining
2020 An Investigation Into Computer-Based Solutions to Support Those With Colour Vision Deficiency to Access Day-to-Day Information, Ph.D., University of Hertfordshire
2019 Image super resolution and interpolation using multi array cameras, Ph.D., University of Bedfordshire
2018 WAVELET-BASED IMAGE AND VIDEO SUPER-RESOLUTION RECONSTRUCTION, Ph.D., Cranfield University
2017 Individual and group dynamic behaviour patterns in bound spaces, Ph.D., London Metropolitan University
2016 Improving image quality via sub-space image super-resolution for low-powered tracking and surveillance systems, MSc by Research, Cranfield University.
Internal Examining
2011 PhD mini viva, Security issues in fourth-generation (4G) networks
2005 Ph.D. viva, Computational Methods for the Operational Surveillance of Nuclear Power Plant
Supervision
2017-Present Ph.D., Investigation into the use of remote sensing to assess condition of rural road networks and assets in low income countries (Part-time)
2014- 2019 Ph.D., Multiview Distributed Video Coding (Full time)
Completed in 2019
2012-2018 Ph.D., Automatic Table Tennis Umpiring (Full time)
Completed in 2018
2012-2016 Ph.D., A Novel Inpainting Framework for Virtual View Synthesis (Full time)
Completed in 2017
2009-2017 Ph.D., New Cross-Layer Processing and Routing Strategies for Cognitive Radio Networks (Part time)
Completed in 2017
2011-2016 Ph.D., A Hybrid Similarity Measure Framework for Multimodal Medical Image Registration (Full time)
Completed in 2016
2008-2015 Ph.D., Intelligent Side Information Generation in Distributed Video Coding (Part time)
Completed in 2015
Teaching interests
He is the module chair of TM255 Communication and information technologies, an author of TM112 Introduction to Computing & IT 2 and a module team member of T215 Communication and Information Technologies. Previously, he chaired the presentation of TM128 Microsoft Server Technologies between 2013 and 2014, T396 Artificial Intelligence for Technology from 2003 to 2007. He was also an author of M366 Natural and Artificial intelligence, T215 Communication and Information Technologies, TM128 Microsoft Server Technologies and TM129 Technologies in practice.
He is leading a 12 month scholarship project investigating the students’ experiences of using virtualisation for their computing practical activities and identified the common difficulties they experienced.
Impact and engagement
In 2024, he led a team competing at the Home Office's Deepfake Detection Challenge. His team came third in the image deepfake category. He is also a member of the Generative AI Specialist Advisory Group of the National Police Chiefs' Council.
In October 2016, Patrick was invited to give a key-note speech on “Automatic Table Tennis Umpiring using a Multi-Agent System” at International Conference on Innovation for Connected World and Smart Living in Hong Kong. Delegates included representatives from Cisco, GP batteries, local businesses and universities.
In 2015, Patrick advised a group of turbine engineers from Alstom and Rolls and Royce in using data modeling technique for managing the transmission of vast amount sensor data. He was subsequently invited to give a talk at a workshop organised by the IET’s turbine network.
Since 2013, Patrick have contributed in organising and running a number of outreach activities including 1 workshop at the Bletchley Park and 3 workshops at National Museum of Computing. On average, each workshop was attended by about 30 people, and were enjoyed by both children and adults.
External collaborations
Patrick works closely with academics from a number of universities in UK and Hong Kong on research projects.
International links
Patrick is a member of the Editorial board of Emerald's Kybernetes (The international journal of cybernetics, systems and management sciences), and is the guest editor of the special issue of Object Detection and Image Classification in the MDPI Applied Sciences journal.
Between 2015 to 2018, he was an executive committee member of the IET's Vision and Imaging Professional network.
Projects
TreeView: developing new capacity for the remote sensing of UK trees and forests
Tree and forest climate interactions are fundamental to a sustainable future and societal wellbeing. Trees are at the heart of the current political discourse, and the UK government is preparing to launch a strategy to accelerate tree planting and improve the management of existing trees and woodlands. The world is becoming increasingly urbanised, and urban trees are well recognised for their environmental, health and wellbeing benefits. Trees across the rural and urban landscape are going to play a central role as we move towards a net-zero emissions economy. The ability to measure, monitor and map the health and status of the UK’s trees is therefore essential to the UK’s future treescape and urban green infrastructure. Currently, tree identification can be achieved with high spatial resolution panchromatic imagery, but we need to go beyond this. We need to be able to not only map species within mixed assemblages, but also characterise the health and size of the trees. Furthermore, we need to be able to measure the particular configurations of urban environments and the small-scale but widespread plantings that are likely to feature prominently in planting programmes. Importantly, we need to be able to monitor changes over time – to quantify carbon sequestration; assess vulnerability and detect the onset of climatic stress or disease outbreak to facilitate early intervention; and to measure the success and monitor compliance of tree planting programmes. This requires going to the spatial scale of tree crowns but capturing the spectral information that will provide the information for classification and characterisation. Advances in both sensors and process understanding is closing the gap between canopy reflectance properties and its functional meaning, opening the possibility of detailed studies at the scale of individual trees and their responses to global change from space. Species identification and mapping has been demonstrated from airborne hyperspectral sensors, enabling species mapping across forests and urban areas. In this project we will push the limits of leading CMOS TDI sensors and optimise system configuration to develop a new platform for the classification, characterisation and monitoring of trees across urban and rural landscapes. Band selection will provide information on both plant health and will feed into classification algorithms developed from extensive ground truthing data. In this pathfinder phase of the project, our objectives are to (could include): 1. Refine band selection based on key vegetation characterisation indices and sensor constraints (from starting point of bands a,b,..f) 2. Develop classification algorithms from airborne hyperspectral data and extensive ground-truthing data sets. 3. Collect new airborne data specifically for one target market: railways 4. Produce the system requirements document for TreeView 5. Produce the mission requirements document for TreeView 6. Perform market analysis of end users across local and national government, commercial and research sectors
Publications
Book Chapter
Cognitive Radio and TV White Space (TVWS) Applications (2019)
Dataset
Exhibition / Performance
Non-Destructive evaluation using ultrasonic technique and distributed Blackboard System (2002)
Journal Article
A multi-view automatic table tennis umpiring framework (2024)
5G multi-layer routing strategies for TV white space secondary user access (2019)
Virtualization for computer networking skills development in a distance learning environment (2018)
A New Dynamic Spectrum Access Algorithm for TV White Space Cognitive Radio Networks (2016)
Tracking Table Tennis Balls in Real Match Scenes for Umpiring Applications (2011)
Presentation / Conference
Identifying tweets from Syria refugees using a Random Forest classifier (2018)
A content-aware quantisation mechanism for transform domain distributed video coding (2018)
Transform domain distributed video coding using larger transform blocks (2018)
Multiview System for Tracking a Fast Moving Object Against Complex Backgrounds (2016)
Tracking a table tennis ball for umpiring purposes using a multi-agent system (2016)
Tracking a table tennis ball for umpiring purposes (2015)
Disocclusion Hole-Filling in DIBR-Synthesized Images using Multi-Scale Template Matching (2014)
Robust Image Registration using Adaptive Expectation Maximisation based PCA (2014)
Joint texture-depth pixel inpainting of disocclusion holes in virtual view synthesis (2013)
Robust retinal image registration using expectation maximisation with mutual information (2013)
Efficient Image Registration using Fast Principal Component Analysis (2012)
A New Mutual Information based Similarity Measure for Medical Image Registration (2012)
A new cross-layer design strategy for TV white space cognitive radio applications (2011)
High-motion table tennis ball tracking for umpiring applications (2010)
Developing an Intelligent Table Tennis Umpiring System: Identifying the ball from the scene (2008)
Developing an intelligent table tennis umpiring system (2007)
Developing an intelligent assistant for table tennis umpires (2007)
DARBS: A Distributed Blackboard System (2001)
Development of a distributed knowledge-based system (2001)
Digital measurement of lightning impulse parameters using curving fitting algorithms (1999)
Update of an early warning fault detection method using artificial intelligence techniques (1997)
Early warning fault detection using artificial intelligent methods (1996)
Power system fault prediction using artificial neural networks (1996)
