Christopher Madden Email & Phone Number

Australia

Melbourne, Australia

Melbourne, Australia

My role investigates the application of the latest Computer Vision and Display research to investigate how realistic synthetic imagery can be. This investigates the use of virtual worlds and other techniques to generate synthetic videos and imagery that can be used to analyse how objects might look in an environment. It will also investigate which steps have a greater impact upon the photo realism, and which steps may have a minimal impact. This can then be used to develop or enhance object detection and analysis techniques, including Computer Vision and Machine Learning approaches.

Melbourne

My role here is to assist DST Group researchers to collaborate on their research tasks with the best external organisations, whether academic, government or industry based. This includes identifying good opportunities for collaboration as well as putting in place the Research contracts. Whilst my role primarily focuses on the Maritime Division, I am part of a group within the Technology Partnerships Office that works across all application domains.

Melbourne

My role has investigated the effective use of unmanned systems in the maritime domain, with a strong focus on the challenging area of underwater robotics. This has included a range of activities on a large underwater vehicle, including software development, systems integration, sensor analysis and piloting the vehicle. My work also involved the development of supporting simulation systems, including simulating virtual maritime environments which can be integrated with a range of modalities, such as large screens, multiple users, and immersive applications, such as using the Occulus Rift. The third component of my work has been to create interesting visualisations of data to collate collections of data so they can be more easily understood by all people, espcially those with a non-scientific background.

My main area of research was investigating techniques for improved sensor analysis, primarily in image and video analysis. The group I worked with had a particular focus upon object analysis in large scale real systems, including fixed and moving surveillance cameras. My work also investigated utilising active platforms, such as intelligent PTZ cameras and mobile robots. This role also involved coordinating the University's component of the MAGIC 2010 entry.

At the University of Technology Sydney, UTS, I conducted a PhD Research project into the Application of Computer Vision techniques to perform semi automated video surveillance across a whole building or campus. This resulted in a PhD thesis titled 'Tracking People Across Disjoint Camera Views' where I enhanced the extraction of a set of height and colour features to improve the capability of a computer system to track the motion of an individual as they were observed periodically around a campus environment in different surveillance cameras. These features could be combined using a combination of error correction and Bayesian fusion techniques to enhance the matching of the individual and build up their track.

Kingston Upon Thames, United Kingdom

My main research project involved the development of a real-time robotic vision system using a range of algorithms for the MOD Grand Challenge. This was a challenging task due to the limited computational power available on a moving platform that was required to be highly automated in a somewhat cluttered human environment. The field trials we produced a working system that participated in the Ministry of Defense organised competition conducted at a UK military site in July 2008. I was also involved in general computer vision and surveillance research projects at the university.

Phd

Diploma Of Leadership And Management

Bachelor

Bachelor