Space-based space surveillance with robust computer vision algorithms. Space-based space surveillance with robust computer vision algorithms. This project aims to develop computer vision algorithms to detect man-made objects in space. These algorithms function on nanosatellite platforms, enabling space-based space surveillance. This technology is expected to provide always-on monitoring of the Earth's orbit to enhance existing defence infrastructure and protect vital space assets, including comm ....Space-based space surveillance with robust computer vision algorithms. Space-based space surveillance with robust computer vision algorithms. This project aims to develop computer vision algorithms to detect man-made objects in space. These algorithms function on nanosatellite platforms, enabling space-based space surveillance. This technology is expected to provide always-on monitoring of the Earth's orbit to enhance existing defence infrastructure and protect vital space assets, including communications and navigational satellites, in Earth’s orbit from collisions and covert sabotage. Increased space use by government and civilian agencies opens up opportunities for the space industry. This project is expected to develop Australia’s space surveillance capabilities, protect space assets and capture a growing market.Read moreRead less
Robust face detection and recognition for computer-based security surveillance. The research aims at improving the existing and creating new automated face detection and recognition methods by making them invariant, firstly to head pose, orientation, scale and rotation, and then to occlusion, lighting conditions and facial expressions.
A robust face detector will be developed first and then a new face recognition algorithm that continues to learn identity-specific discriminants on-line by co ....Robust face detection and recognition for computer-based security surveillance. The research aims at improving the existing and creating new automated face detection and recognition methods by making them invariant, firstly to head pose, orientation, scale and rotation, and then to occlusion, lighting conditions and facial expressions.
A robust face detector will be developed first and then a new face recognition algorithm that continues to learn identity-specific discriminants on-line by collecting incremental face exemplars. The result of the research will be an algorithm that can improve its performance on-line adapting in a stable learning process each identity model to the correct facial examples.
The research has significant practical implication in visual surveillance increasing the robustness of identification of person identity, state and intent.
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Methodologies for automatic visual identification in heat detection aids. New techniques will be designed and developed to automate the existing manual heat detection of cattle, under general imaging conditions. The proposed intelligent system will consist of six stages: 1- image acquisition, 2- image preprocessing, 3- presence detection, 4- illumination compensation, 5- HD detection, and 6- heat detection. The proposed system will handle various image variations, and will be fast and cost-effec ....Methodologies for automatic visual identification in heat detection aids. New techniques will be designed and developed to automate the existing manual heat detection of cattle, under general imaging conditions. The proposed intelligent system will consist of six stages: 1- image acquisition, 2- image preprocessing, 3- presence detection, 4- illumination compensation, 5- HD detection, and 6- heat detection. The proposed system will handle various image variations, and will be fast and cost-effective. The developed system will improve the productivity of Australian cattle industry.Read moreRead less
Reconfigurable System-on-Chip for Computer Network Appliances. As Internet connectivity becomes ubiquitous, so does the need for computer network security. As algorithms become more sophisticated, and network speeds increase, software-only implementations of network security applications become less feasible on small, embedded network appliances. This project investigates new computer architectures, based on reconfigurable System-on-Chip technology, which can improve algorithm speed through sp ....Reconfigurable System-on-Chip for Computer Network Appliances. As Internet connectivity becomes ubiquitous, so does the need for computer network security. As algorithms become more sophisticated, and network speeds increase, software-only implementations of network security applications become less feasible on small, embedded network appliances. This project investigates new computer architectures, based on reconfigurable System-on-Chip technology, which can improve algorithm speed through specialised instruction sets, hardware accelerators, and parallel processing. Research outcomes will be commercialised by the project's industry partner - a global leader in low-cost network security appliances.Read moreRead less
Improving yield through image-based structural analysis of cereals. Feeding an increasing world population under the threat of climate change requires the development of new plant varieties capable of delivering higher yield in more marginal conditions. This project will develop image-based technologies for accurately estimating plant yield which will improve the effectiveness of plant breeding processes.
Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing ....Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing the human contact with animals are of high priority in the development of this Australian-led emerging industry. The project aims to develop technology to bring this world- first aquaculture factory to large scale production, and create new export opportunities for lobsters and production systems.Read moreRead less
Accessing Australia's photographic history. This project aims to bring to life the rich historical record that is stored in our museum's collections of photographs. Using novel image analysis techniques, this project will enable the creation of three-dimensional models from these photographs, which can then be used for public exhibits or viewed interactively at home through a web browser.
Semantic change detection through large-scale learning. This project aims to develop technologies which understand the content of images before higher-level analysis is performed. This approach is intended to allow more accurate and reliable decisions to be made using automated image analysis than has previously been possible. The project will particularly investigate the detection of change in the contents of an image.
Application of manifold-based image analysis to identify subtle changes in digitally-captured pathology samples. This project will research and develop advanced computer aided analytics for digital pathology with the aim of automating several common pathology tests. This project should not only greatly increase the speed of pathology tests but should also improve quality, lower costs and improve patient outcomes.
Fruit shape estimation from stereoscopic images in real time. The research aims at improving the process of automatic fruit inspection and classification.
Existing stereo vision algorithms to extract depth information are unsuitable for real time calculations.
The increasing complexity and reducing cost of field programmable gate arrays along with the development of algorithms that have a high degree of parallelism and locality has created
the possibility of performing the calculation ....Fruit shape estimation from stereoscopic images in real time. The research aims at improving the process of automatic fruit inspection and classification.
Existing stereo vision algorithms to extract depth information are unsuitable for real time calculations.
The increasing complexity and reducing cost of field programmable gate arrays along with the development of algorithms that have a high degree of parallelism and locality has created
the possibility of performing the calculations required in real time.
This projects aims to investigate the suitability of the various stereo vision algorithms available in the literature for real time hardware implementation with application to fruit shape estimation it real time.
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