A data driven paradigm for service-oriented system engineering. This project aims to design and develop a data driven paradigm for service-oriented system engineering that allows system engineers and domain experts in different domains to build software systems easily in order to enable fast technology transfer within and across domain boundaries. This model integrates and automates a suite of efficient approaches for system structure determination, validation and recommendation based on keyword ....A data driven paradigm for service-oriented system engineering. This project aims to design and develop a data driven paradigm for service-oriented system engineering that allows system engineers and domain experts in different domains to build software systems easily in order to enable fast technology transfer within and across domain boundaries. This model integrates and automates a suite of efficient approaches for system structure determination, validation and recommendation based on keyword search, subgraph isomorphism and substructure query techniques. This project is expected to significantly accelerate the application of new technologies, for example, big data analytics and Internet of Things, in many of Australia's critical domains such as e-Health, smart cities, and cybersecurity.Read moreRead less
Learning to see in 3D. The project aims to endow machine vision with an ability we, as humans, use almost constantly: to judge 3D properties from a 2D image. This extremely useful ability will be applied to digital images to obtain 3D measurements and aid in automating tasks such as mining, surveying, medical diagnosis, and visual effects in movies.
Recognising and reconstructing objects in real time from a moving camera. This project will use a moving camera to estimate the three-dimensional shape and identity of objects and surfaces it can see. This ability, which we humans use all the time, has wide application in automation including driver assistance, exploring hazardous environments, robotics, remote collaboration, and the creation of three-dimensional models for entertainment.
Optimal Robust Fitting under the Framework of LP-Type Problems. The project aims to develop algorithms to support the development of robust and accurate computer vision systems. Real-world visual data (images, videos) is inherently noisy and outlier prone. To build computer vision systems that work reliably in the real world, it is necessary to ensure that the underlying algorithms are robust and efficient. The project aims to devise novel algorithms that can compute the best possible result giv ....Optimal Robust Fitting under the Framework of LP-Type Problems. The project aims to develop algorithms to support the development of robust and accurate computer vision systems. Real-world visual data (images, videos) is inherently noisy and outlier prone. To build computer vision systems that work reliably in the real world, it is necessary to ensure that the underlying algorithms are robust and efficient. The project aims to devise novel algorithms that can compute the best possible result given the input data in a short amount of time. The expected outcomes would support the construction of reliable and accurate computer vision-based systems, such as large-scale 3-D reconstruction from photo collections, self-driving cars and domestic robots.Read moreRead less
Whole image understanding by convolutions on graphs. This project seeks to develop technologies that will help computer vision interpret the whole visible scene, rather than just some of the objects therein. Existing automated methods for understanding images perform well at recognising specific objects in canonical poses, but the problem of whole image interpretation is far more challenging. Convolutional neural networks (CNN) have underpinned recent progress in object recognition, but whole-im ....Whole image understanding by convolutions on graphs. This project seeks to develop technologies that will help computer vision interpret the whole visible scene, rather than just some of the objects therein. Existing automated methods for understanding images perform well at recognising specific objects in canonical poses, but the problem of whole image interpretation is far more challenging. Convolutional neural networks (CNN) have underpinned recent progress in object recognition, but whole-image understanding cannot be tackled similarly because the number of possible combinations of objects is too large. The project thus proposes a graph-based generalisation of the CNN approach which allows scene structure to be learned explicitly. This would represent an important step towards providing computers with robust vision, allowing them to interact with their environment.Read moreRead less
Model-based error location in Java programs. The construction of modern software requires extensive testing and
debugging in addition to using appropriate specification, design, and
verification techniques. Testing and debugging are very time-consuming
and costly, drawing - according to recent articles - "typically 50%
or more of the resources for software projects''. By providing a new,
flexible approach to the debugging of complex software, this project
offers the potential of significant cost ....Model-based error location in Java programs. The construction of modern software requires extensive testing and
debugging in addition to using appropriate specification, design, and
verification techniques. Testing and debugging are very time-consuming
and costly, drawing - according to recent articles - "typically 50%
or more of the resources for software projects''. By providing a new,
flexible approach to the debugging of complex software, this project
offers the potential of significant cost savings, highly beneficial to
the ICT industry. Lessons learned from the demonstration prototype,
can be directly carried over into commercial tool development. In
addition, the project strengthens links to high quality European
research laboratories.Read moreRead less
Model-based error location in concurrent software. The construction of modern software requires extensive testing and debugging in addition to using appropriate specification, design, and verification techniques. Testing and debugging are very time-consuming and costly, drawing - according to recent articles - ``typically 50\% or more of the resources for software projects''. By extending the power of a new, flexible debugging approach, this project offers the potential of significant cost savin ....Model-based error location in concurrent software. The construction of modern software requires extensive testing and debugging in addition to using appropriate specification, design, and verification techniques. Testing and debugging are very time-consuming and costly, drawing - according to recent articles - ``typically 50\% or more of the resources for software projects''. By extending the power of a new, flexible debugging approach, this project offers the potential of significant cost savings, highly beneficial to any industry with a significant ICT component, e.g., defense. Lessons learned from the demonstration prototype, can be directly carried over into commercial tool development. The project strengthens links to high quality European research laboratories.Read moreRead less
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
Efficient data mining methods for evidence-based decision making. This project aims to develop efficient data mining methods for causal predictions. Evidence-based decision making (EBD), such as evidence-based medicine and policy, is always preferable. To support EBD, causal predictions forecast how outcomes change when conditions are manipulated. Progress has been made in theoretical research on causal inference based on observational data, but few methods can automatically mine causal signals ....Efficient data mining methods for evidence-based decision making. This project aims to develop efficient data mining methods for causal predictions. Evidence-based decision making (EBD), such as evidence-based medicine and policy, is always preferable. To support EBD, causal predictions forecast how outcomes change when conditions are manipulated. Progress has been made in theoretical research on causal inference based on observational data, but few methods can automatically mine causal signals from the data and methods for efficient causal predictions based on data are even fewer. This project will apply its methods to biomedical problems. The outcomes could support smart and data-driven evidence based decision making in many areas, such as therapeutics and government policy making.Read moreRead less
Early detection of component incompatibility in time-dependent computer architectures. Complex real-time systems are increasingly being built by integrating off-the-shelf components. There are obvious benefits to this approach, but the hidden costs associated with integration are still a major problem. Our proposed approach will enable early detection of integration problems, and thus provide potential for large cost savings. This brings with it clear benefits to industry. One industry that woul ....Early detection of component incompatibility in time-dependent computer architectures. Complex real-time systems are increasingly being built by integrating off-the-shelf components. There are obvious benefits to this approach, but the hidden costs associated with integration are still a major problem. Our proposed approach will enable early detection of integration problems, and thus provide potential for large cost savings. This brings with it clear benefits to industry. One industry that would benefit by such technology is the Australian Navy, which is increasingly being confronted with the challenge of integrating off-the-shelf components in large Naval Combat Systems. Read moreRead less