Statistical Methods of Model Fitting and Segmentation in Computer Vision. Electronic sensors such as cameras and lasers can provide a rich source of information about the position, shape, and motion of objects around us. However, to extract this information in a reliable, automatic, and accurate way requires a sophisticated statistical theory of the process. Example applications include: video surveillance (better automatic detection of moving people and vehicles and of characterising what those ....Statistical Methods of Model Fitting and Segmentation in Computer Vision. Electronic sensors such as cameras and lasers can provide a rich source of information about the position, shape, and motion of objects around us. However, to extract this information in a reliable, automatic, and accurate way requires a sophisticated statistical theory of the process. Example applications include: video surveillance (better automatic detection of moving people and vehicles and of characterising what those people and vehicles are doing), industrial prototyping and inspection (measuring the size and shape of objects), urban planning (laser scanning streetscapes to create computer models of cities), entertainment industry (movie special effects and games), etc. Read moreRead less
Advanced Interface Technologies for Computational Science & Simulation. The project will research novel computer vision technologies that enable the next generation of visualisation portals for scientific collaboration. The development of new computer vision tools is key to truly natural human-machine interaction. The research outcomes of this project directly align with National Research Priority 3: Frontier Technologies. It supports four of the five relevant priority goals - Breakthrough Scien ....Advanced Interface Technologies for Computational Science & Simulation. The project will research novel computer vision technologies that enable the next generation of visualisation portals for scientific collaboration. The development of new computer vision tools is key to truly natural human-machine interaction. The research outcomes of this project directly align with National Research Priority 3: Frontier Technologies. It supports four of the five relevant priority goals - Breakthrough Science, Frontier Technologies, Smart Information Use, and Promoting an Innovation Culture and Economy. Outcomes of this research are also relevant to Research Priority 4: Safeguarding Australia, and has direct applications to video surveillance technology. Significant commercial opportunities, including licensing and spin-offs exist.Read moreRead less
New techniques for modelling, diagnosis and counter measures for cardiac related sleep disordered breathing. Around 50% of congestive heart failure sufferers have some form of sleep disordered breathing. However, little has been done so far to simultaneously monitor, analyse and treat the two conditions. Therefore, this project proposes to develop new technology incorporating mathematical models for heart rate variability, considering the links between sleep disordered breathing and cardiovasc ....New techniques for modelling, diagnosis and counter measures for cardiac related sleep disordered breathing. Around 50% of congestive heart failure sufferers have some form of sleep disordered breathing. However, little has been done so far to simultaneously monitor, analyse and treat the two conditions. Therefore, this project proposes to develop new technology incorporating mathematical models for heart rate variability, considering the links between sleep disordered breathing and cardiovascular disease. This innovation will enable, for the first time, a device capable of accurate and reliable diagnosis of various sleep disorders using only conventional ECG data. Such technology has the potential to produce significant community health benefits, and save several millions of lives worldwide.Read moreRead less
A Novel System for Surveillance of Moving Objects. Surveillance of moving objects is critical in numerous applications such as detection and recognition of motor vehicles. It is important for detection to be fast and accurate with low cost. In this project, we aim to implement a surveillance system consisting of an efficient algorithm on a PC network with a camera. Our detection algorithm will be achieved with an advanced and computationally powerful image representation for fast computation. It ....A Novel System for Surveillance of Moving Objects. Surveillance of moving objects is critical in numerous applications such as detection and recognition of motor vehicles. It is important for detection to be fast and accurate with low cost. In this project, we aim to implement a surveillance system consisting of an efficient algorithm on a PC network with a camera. Our detection algorithm will be achieved with an advanced and computationally powerful image representation for fast computation. Its accuracy will be enhanced by adapting a well recognized theory for fast removal of image noise. Our implementation on the PC network will provide a flexible and extensible platform for parallel computing to further reduce detection time while keeping costs low.Read moreRead less
Detecting, Locating and Tracking Human Faces using Skin Colour. With growing concerns for national security and public safety, government agencies in Australia and around the world are taking strong measures to introduce biometric-enhanced official identification documents such as passports, visas, and ID cards. The proposed face detection and tracking system will play a key role in personal identification and human activity monitoring. The developed system will have a huge potential in surveill ....Detecting, Locating and Tracking Human Faces using Skin Colour. With growing concerns for national security and public safety, government agencies in Australia and around the world are taking strong measures to introduce biometric-enhanced official identification documents such as passports, visas, and ID cards. The proposed face detection and tracking system will play a key role in personal identification and human activity monitoring. The developed system will have a huge potential in surveillance, security, law enforcement, and ICT. This project will contribute to building a knowledge economy in Australia and help safeguard and protect Australia from terrorism and crime. Furthermore, its outcomes will enhance the reputation of Australia as a leader in frontier technologies and smart information use.Read moreRead less
Network Intrusion Detection via Machine Learning. Computer security is an increasingly important, yet complex task. It
takes significant skills to configure systems properly such that they
are safe from malicious attacks.
The proposed project aims at designing automatic systems which are
able to adapt to an existing network configuration and which detect
novel and unusual events. For this purpose we will use modern machine
learning techniques, mainly based on kernels. In particular, rec ....Network Intrusion Detection via Machine Learning. Computer security is an increasingly important, yet complex task. It
takes significant skills to configure systems properly such that they
are safe from malicious attacks.
The proposed project aims at designing automatic systems which are
able to adapt to an existing network configuration and which detect
novel and unusual events. For this purpose we will use modern machine
learning techniques, mainly based on kernels. In particular, recently
developed algorithms to estimate the support of a distribution and
detect rare events will be employed in this context.
The project is in cooperation with Dr. Ralf Herbrich (Microsoft
Research, Cambridge).
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Pattern Recognition and Scene Analysis via Machine Learning. We plan to use kernel methods, a novel machine learning technique, for computer vision problems, such as scene analysis and real time object recognition. Such capabilities are relevant for the design of intelligent and adaptive systems, suitable for complex real world environments. Expected outcomes are the design of efficient statistical tools which take the special nature of visual data into account (structure, decomposition, prior ....Pattern Recognition and Scene Analysis via Machine Learning. We plan to use kernel methods, a novel machine learning technique, for computer vision problems, such as scene analysis and real time object recognition. Such capabilities are relevant for the design of intelligent and adaptive systems, suitable for complex real world environments. Expected outcomes are the design of efficient statistical tools which take the special nature of visual data into account (structure, decomposition, prior knowledge of physical environments, etc.) and combine the advantages of feature based high-level vision methods with low-level machine learning techniques.
This proposal is part of a joint IST project with partners from the European Union.Read moreRead less
Generic Content-based News Picture Retrieval with Local Invariant Features. Image Retrieval searches for images from large databases whose visual content meets the requirements submitted by users. Besides directly benefiting the Partner Organization, this project will enable more efficient access to large picture repositories in news agencies and publishers, digital libraries and film archives. It will make public use of visual information much more convenient and economical. It will help securi ....Generic Content-based News Picture Retrieval with Local Invariant Features. Image Retrieval searches for images from large databases whose visual content meets the requirements submitted by users. Besides directly benefiting the Partner Organization, this project will enable more efficient access to large picture repositories in news agencies and publishers, digital libraries and film archives. It will make public use of visual information much more convenient and economical. It will help security officers to effortlessly and accurately find particular scenes from the images generated by a large closed-circuit TV networks. Also, the developed technology can be applied to tele-education and e-commerce. New algorithms developed in this project will benefit the Australian and world scientific communities.Read moreRead less
ARC Centre for Perceptive & Intelligent Machines in Complex Environments. The Centre for Perceptive and Intelligent Machines in Complex Environments will perform fundamental research into and construct reliable large-scale systems of networked sensors, computational intelligence, mobile robots, and knowledge sources to support a large variety of critical human tasks, including surveillance/ security (eg. borders/airports/homes), health care support (eg. smart houses/ health condition monitoring, ....ARC Centre for Perceptive & Intelligent Machines in Complex Environments. The Centre for Perceptive and Intelligent Machines in Complex Environments will perform fundamental research into and construct reliable large-scale systems of networked sensors, computational intelligence, mobile robots, and knowledge sources to support a large variety of critical human tasks, including surveillance/ security (eg. borders/airports/homes), health care support (eg. smart houses/ health condition monitoring, semi autonomous wheelchairs), and civil disaster support (eg. fighting bushfires, looking for people in rubble) always keeping people in the loop so that strong human/ machine cooperative ventures can achieve what neither human or machines could accomplish independently.Read moreRead less
Understanding cortical processing: Neuronal activity and learning in recurrently connected networks. This project addresses fundamental cross-disciplinary issues of information processing and control in large-scale biological neural systems. This is an area of research that is at the cutting edge of intelligent processing systems. An understanding of these mechanisms would have considerable implications in areas that span a range of complex biological and artificial neural systems, including the ....Understanding cortical processing: Neuronal activity and learning in recurrently connected networks. This project addresses fundamental cross-disciplinary issues of information processing and control in large-scale biological neural systems. This is an area of research that is at the cutting edge of intelligent processing systems. An understanding of these mechanisms would have considerable implications in areas that span a range of complex biological and artificial neural systems, including the rapidly growing fields of robotics, machine learning, and adaptive control, all with applications in diverse areas of economic importance. The project will provide students with training at an international level within Australia, thus helping ensure Australia maintains and extends its science and technology base.Read moreRead less