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
Automated texture selection and classification methods for detection of osteoarthritis in knee radiographs. In Australia there are 1-2 million OA sufferers, a condition that costs approximately $9 billion annually. This project will address an important problem of early detection and monitoring of OA and this remains in line with the National Research Priority 2. Potential outcomes of the project will result in better diagnosis and treatment of OA, reduced discomfort to the individual and saving ....Automated texture selection and classification methods for detection of osteoarthritis in knee radiographs. In Australia there are 1-2 million OA sufferers, a condition that costs approximately $9 billion annually. This project will address an important problem of early detection and monitoring of OA and this remains in line with the National Research Priority 2. Potential outcomes of the project will result in better diagnosis and treatment of OA, reduced discomfort to the individual and saving to the national economy. This project will improve existing activity and rehabilitation programs such as exercise of lower limbs and it will help in developing diets for healthy people and OA sufferers.Read moreRead less
Unifying Modern Approaches in Machine Learning. The proposed research will lead to better algorithms for some important machine learning problems that could lead to better tools for extracting useful knowledge from data such as in bioinformatics and sensor networks; it will strengthen an international collaboration with one of the world's top centres of machine learning research; it will contribute to an open source toolkit of machine learning algorithms which will put Australia on the map as a ....Unifying Modern Approaches in Machine Learning. The proposed research will lead to better algorithms for some important machine learning problems that could lead to better tools for extracting useful knowledge from data such as in bioinformatics and sensor networks; it will strengthen an international collaboration with one of the world's top centres of machine learning research; it will contribute to an open source toolkit of machine learning algorithms which will put Australia on the map as a provider of sophisticated machine learning software; it will provide training opportunities for several PhD students and a postdoc to work with some of the best machine learning researchers in the world.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
Unified Representations of Multimodal Biometrics for Robust Authentication and Identification. We propose two biometric systems based on two novel unified multimodal biometric representations. These systems will have a great potential impact on the national economy by reducing frauds related to identity, credit card transactions, and ATM withdrawals. Statistics show that these types of frauds are dramatically increasing in the U.S.A., the U.K., and Australia. Our systems will also have governmen ....Unified Representations of Multimodal Biometrics for Robust Authentication and Identification. We propose two biometric systems based on two novel unified multimodal biometric representations. These systems will have a great potential impact on the national economy by reducing frauds related to identity, credit card transactions, and ATM withdrawals. Statistics show that these types of frauds are dramatically increasing in the U.S.A., the U.K., and Australia. Our systems will also have government applications and will impact on the national security in areas related to immigration, passport and driver's license controls. Forensic applications include criminal identification, crime scene investigation and corpse identification (as in the case of the victims of the Asian tsunami 2004). Read moreRead less
Automatic Recognition of Human Activities in Surveillance Videos: Overcoming the Curse of Dimensionality. This project will deliver a technology capable of automatically recognising human activities of interest in surveillance videos. The project will tackle the challenging, huge complexity inherent in the recognition of human activities by novel statistical pattern recognition techniques. The outcome of this project will be an effective activity recognition technology that will help monitor the ....Automatic Recognition of Human Activities in Surveillance Videos: Overcoming the Curse of Dimensionality. This project will deliver a technology capable of automatically recognising human activities of interest in surveillance videos. The project will tackle the challenging, huge complexity inherent in the recognition of human activities by novel statistical pattern recognition techniques. The outcome of this project will be an effective activity recognition technology that will help monitor the security and safety of environments and support the further development of the Australian video surveillance industry.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
Special Research Initiatives - Grant ID: SR0567196
Funder
Australian Research Council
Funding Amount
$55,000.00
Summary
Improved early detection of breast cancer enabled by grid-computing and advanced modelling and visualisation of MR images. This project will investigate the utility of grid computing in the detection of breast cancer from magnetic resonance (MR) images. The large quantity of data acquired using MR imaging is difficult for clinicians to review and the cost of missed or incorrect detection is high. To provide rapid visualisation and assessment of the acquired data, grid computing will be used in c ....Improved early detection of breast cancer enabled by grid-computing and advanced modelling and visualisation of MR images. This project will investigate the utility of grid computing in the detection of breast cancer from magnetic resonance (MR) images. The large quantity of data acquired using MR imaging is difficult for clinicians to review and the cost of missed or incorrect detection is high. To provide rapid visualisation and assessment of the acquired data, grid computing will be used in conjunction with interactive visualisation with haptic feedback. Grid computing experience and haptic device expertise will be achieved via Swedish collaborators. The successful outcome of this project will be software for the production of 3D colour-coded breast images in which suspicious regions are highlighted and can be physically interrogated using the haptic device.Read moreRead less
Automatic real-time detection of infiltrated objects for security of airports and train stations. Infiltrated objects represent a very high security threat in critical areas such as airports and train stations. In order to neutralise such a threat, this project will develop new automatic technologies capable of detecting infiltrated objects in sensitive areas in real time, analysing the movements of their original carriers in the nearby areas, and raising attention accordingly. The technologies ....Automatic real-time detection of infiltrated objects for security of airports and train stations. Infiltrated objects represent a very high security threat in critical areas such as airports and train stations. In order to neutralise such a threat, this project will develop new automatic technologies capable of detecting infiltrated objects in sensitive areas in real time, analysing the movements of their original carriers in the nearby areas, and raising attention accordingly. The technologies will be based on the automatic analysis of camera videos made by computers without the need for assessing or storing the identities of common passers-by. The potential of application is huge extending beyond airports and train stations to any public areas.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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