Tracking targets in large scale surveillance camera networks. The research is expected to provide a significant boost in the effectiveness of safety and security measures for public facilities and open spaces that are monitored by surveillance cameras. The general public benefits from this through a decreased need for intrusive security measures, and increased deterrence of crime and anti-social behaviour. This capability is in demand worldwide for both public and private camera networks, whose ....Tracking targets in large scale surveillance camera networks. The research is expected to provide a significant boost in the effectiveness of safety and security measures for public facilities and open spaces that are monitored by surveillance cameras. The general public benefits from this through a decreased need for intrusive security measures, and increased deterrence of crime and anti-social behaviour. This capability is in demand worldwide for both public and private camera networks, whose usefulness is currently limited by the difficulty of monitoring them. We therefore anticipate considerable commercial interest in Australia and internationally.
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Deep visual understanding: learning to see in an unruly world. Deep Learning has achieved incredible success at an astonishing variety of Computer Vision tasks recently. This project aims to convey this success into the challenging domain of high-level image-based reasoning. It will extend deep learning to achieve flexible semantic reasoning about the content of images based on information gleaned from the huge volumes of data available on the Internet. The project expects to overcome one of the ....Deep visual understanding: learning to see in an unruly world. Deep Learning has achieved incredible success at an astonishing variety of Computer Vision tasks recently. This project aims to convey this success into the challenging domain of high-level image-based reasoning. It will extend deep learning to achieve flexible semantic reasoning about the content of images based on information gleaned from the huge volumes of data available on the Internet. The project expects to overcome one of the primary limitations of deep learning and will greatly increase its practical application to a range of industrial, cultural or health settings.Read moreRead less
Added depth: automated high level image interpretation. Humans are very good at understanding the world through imagery, but computers lack this fundamental capacity because they lack experience of what they might see. This project will provide this experience by combining the large volumes of imagery on the Internet with three dimensional information generated by humans for other purposes.
Making Meta-learning Generalised . This project aims to develop novel machine learning techniques, termed generalised meta-learning, to make machines better utilise past experience to solve new tasks with few data. It expects to reduce the undesirable dependence of current machine learning on labelled data and significantly expand its application scope. Expected outcomes of the project consist of new theoretical results on meta-learning and a set of innovative algorithms that can support the bui ....Making Meta-learning Generalised . This project aims to develop novel machine learning techniques, termed generalised meta-learning, to make machines better utilise past experience to solve new tasks with few data. It expects to reduce the undesirable dependence of current machine learning on labelled data and significantly expand its application scope. Expected outcomes of the project consist of new theoretical results on meta-learning and a set of innovative algorithms that can support the building of next generation of computer vision systems to work in open and dynamic environments. This should be able to produce solid benefits to the science, society, and economy of Australian via the application of these advanced intelligent systems.Read moreRead less
Intelligent and objective measurement of wool fibre diameter. More than a half million tones of wool produced in Australia per year are visually evaluated by human woolclassers. This fibre-classing process is subjective and heavily dependent on the experience of the classers. In this project, we will objectively measure wool fibre diameter by extracting features used by human woolclassers and by combining image processing and artificial intelligence. The fractal dimension calculated by fracta ....Intelligent and objective measurement of wool fibre diameter. More than a half million tones of wool produced in Australia per year are visually evaluated by human woolclassers. This fibre-classing process is subjective and heavily dependent on the experience of the classers. In this project, we will objectively measure wool fibre diameter by extracting features used by human woolclassers and by combining image processing and artificial intelligence. The fractal dimension calculated by fractal based texture analysis will be correlated to fibre diameter. This approach will provide an insight into an on farm and/or in shed objective measurement of wool fibre diameter.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
Investigation and development of robust rule discovery and classification system. This research focuses on a national research priority, namely smart information use. The expected outcomes of the project will greatly advance intelligent system design, such as automatic decision making, fault detection and problem diagnosis, for finance, medical, telecom and many other areas. It has great potential for commercialisation and earning incomes for the future research. The publications will benefit th ....Investigation and development of robust rule discovery and classification system. This research focuses on a national research priority, namely smart information use. The expected outcomes of the project will greatly advance intelligent system design, such as automatic decision making, fault detection and problem diagnosis, for finance, medical, telecom and many other areas. It has great potential for commercialisation and earning incomes for the future research. The publications will benefit the future development of intelligent systems for dealing with missing data. This project directly supports a PhD student and two research assistants who will most likely continue their higher degree study. These contribute to regional tertiary education.Read moreRead less
Autocalibration without decimation. The insertion of computer generated characters into real footage, the removal of objects from video, and the recovery of 3-dimensional architectural or topographic models from photographs are amongst a growing number of processes used in industry which require highly accurate camera calibration. Autocalibration is thus a prerequisite for these and many other emerging image-based technologies. By developing expertise in this area, and particularly by enabling ....Autocalibration without decimation. The insertion of computer generated characters into real footage, the removal of objects from video, and the recovery of 3-dimensional architectural or topographic models from photographs are amongst a growing number of processes used in industry which require highly accurate camera calibration. Autocalibration is thus a prerequisite for these and many other emerging image-based technologies. By developing expertise in this area, and particularly by enabling more flexible and efficient means of autocalibration, we expect to provide Australian industry with a valuable improvement in the state of the art and a competitive edge in a number of important application areas.Read moreRead less
Combined shape and appearance descriptors for visual object recognition. The quantity of video generated each year is expanding rapidly. This increasing volume of visual information means that it is more likely that any particular event will be recorded, but that the footage will be harder to find. This applies to a collection of home videos as much as to television and movie footage. The object-recognition method to be developed has the potential to alleviate this situation, in which vast amou ....Combined shape and appearance descriptors for visual object recognition. The quantity of video generated each year is expanding rapidly. This increasing volume of visual information means that it is more likely that any particular event will be recorded, but that the footage will be harder to find. This applies to a collection of home videos as much as to television and movie footage. The object-recognition method to be developed has the potential to alleviate this situation, in which vast amounts of video data are available but have little value. Such an outcome would be a boon for Australian industry and offer a valuable export opportunity.Read moreRead less
Multi-objective parameter estimation techniques for computer vision. This project will benefit Australia's scientific knowledge and technology base in the area of computer vision. By contributing improved methods for parameter estimation applicable to a wide variety of technical problems, the project will aid the generation of improved software products in a wide variety of domains. Examples include: augmented reality systems, with which virtual reality artifacts may be immersed within real vid ....Multi-objective parameter estimation techniques for computer vision. This project will benefit Australia's scientific knowledge and technology base in the area of computer vision. By contributing improved methods for parameter estimation applicable to a wide variety of technical problems, the project will aid the generation of improved software products in a wide variety of domains. Examples include: augmented reality systems, with which virtual reality artifacts may be immersed within real video; 3D from 2D systems, with which 3D object structure may be computed from image streams; and visual robotic systems, with which the pose of viewed objects may be determined.Read moreRead less