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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Intruder alert! detecting and classifying events in noisy time series. This project aims to address the mathematical challenges in automated early detection and classification of intrusion events in noisy time series generated from perimeter security systems. The project expects to develop robust methods to detect intrusion events under different operating environments while ignoring nuisance events. The project will boost the global competitiveness of the Australian security industry, and enabl ....Intruder alert! detecting and classifying events in noisy time series. This project aims to address the mathematical challenges in automated early detection and classification of intrusion events in noisy time series generated from perimeter security systems. The project expects to develop robust methods to detect intrusion events under different operating environments while ignoring nuisance events. The project will boost the global competitiveness of the Australian security industry, and enable improved event detection and classification in noisy time series to the benefit of many critical application areas beyond national security.Read moreRead less
Non-Contact In-process Shape Measurement of Windscreens. Optical techniques have been widely used for non-contact measurement of the 3-D shape of diffusely reflecting surfaces. However, there is no evidence for the successful implementation of a real-time shape measurement system for large specular surfaces, despite the many important industrial applications. The aim of this project is to develop optically-based techniques to measure the shape of specular and transparent surfaces in real time in ....Non-Contact In-process Shape Measurement of Windscreens. Optical techniques have been widely used for non-contact measurement of the 3-D shape of diffusely reflecting surfaces. However, there is no evidence for the successful implementation of a real-time shape measurement system for large specular surfaces, despite the many important industrial applications. The aim of this project is to develop optically-based techniques to measure the shape of specular and transparent surfaces in real time in an industrial environment. The main outcome of the research will be a prototype on-line shape measurement system to control the quality of car windscreens.Read moreRead less
Privacy-preserving cloud data mining-as-a-service. This project aims to explore practical privacy-preserving solutions for cloud data mining-as-a-service based on the Intel Software Guard Extensions (SGX) technology. The research addresses privacy concerns of users when outsourcing data mining needs to the cloud. These concerns have increased as more businesses evaluate data mining-as-an outsourced service due to lack of expertise or computation resources. The expected outcomes from the research ....Privacy-preserving cloud data mining-as-a-service. This project aims to explore practical privacy-preserving solutions for cloud data mining-as-a-service based on the Intel Software Guard Extensions (SGX) technology. The research addresses privacy concerns of users when outsourcing data mining needs to the cloud. These concerns have increased as more businesses evaluate data mining-as-an outsourced service due to lack of expertise or computation resources. The expected outcomes from the research will include new data privacy models, new privacy-preserving data mining algorithms, and a prototype of cloud data mining software. These will help businesses cut costs for data mining and privacy protection, and provide significant benefits toward helping Australia achieve its national cyber security strategy and potentially provide economic impact from commercialisation of new software technology for the industry partner.Read moreRead less
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
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
Building a Smart Diagnostic System for Low Back Ailments. This research will develop an early back ailment diagnostic system that will reduce the recurrence of low back pain, and hence reduce the cost to the health system. This is significant to the community from prevention of pain, to the health care system that spends billions of dollars combating this modern day ailment and towards the industry where the low back pain is the single largest reason for sick leave in Australia. It will also giv ....Building a Smart Diagnostic System for Low Back Ailments. This research will develop an early back ailment diagnostic system that will reduce the recurrence of low back pain, and hence reduce the cost to the health system. This is significant to the community from prevention of pain, to the health care system that spends billions of dollars combating this modern day ailment and towards the industry where the low back pain is the single largest reason for sick leave in Australia. It will also give rise to employment of skilled technical people and an opportunity to increase high-value exports from Australia.Read moreRead less
Privacy Preserving Data Sharing in Electronic Health Environment. This project aims to improve access to electronic health data (EHD) while still ensuring patient privacy. EHD can provide important information for medical research and health-care resource allocations. However, data sharing in electronic health environments is challenging because of the privacy concerns of customers. Large-scale unauthorised access from internal staff has been reported in Medicare. This project aims to develop ne ....Privacy Preserving Data Sharing in Electronic Health Environment. This project aims to improve access to electronic health data (EHD) while still ensuring patient privacy. EHD can provide important information for medical research and health-care resource allocations. However, data sharing in electronic health environments is challenging because of the privacy concerns of customers. Large-scale unauthorised access from internal staff has been reported in Medicare. This project aims to develop new privacy-preserving algorithms on EHD database federations, which can provide efficient data access yet block inside attacks. It will significantly improve the data available for medical research, while reducing the cost of EHD system management and providing visualised decision supports to medical staff and the government health resource planners.Read moreRead less
Damage Detection and Quantification using Infrastructure Digital Twins. Structural health monitoring is vital for infrastructure assets management as early detection of structural conditions is key to both safety and ongoing maintenance. This project combines computer vision, vibration tests, finite element modelling and deep learning technologies to develop an efficient structural health monitoring system. Digital twins created from images taken by cameras or UAVs will be correlated through dee ....Damage Detection and Quantification using Infrastructure Digital Twins. Structural health monitoring is vital for infrastructure assets management as early detection of structural conditions is key to both safety and ongoing maintenance. This project combines computer vision, vibration tests, finite element modelling and deep learning technologies to develop an efficient structural health monitoring system. Digital twins created from images taken by cameras or UAVs will be correlated through deep learning with structural conditions and load-carrying capacities obtained from vibration tests and finite element model analysis for efficient structural damage detection and quantification. The project will lead to effective structural health monitoring and enhance structural safety and reduce maintenance costs. Read moreRead less
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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