Using shape change for object perception: human and artificial vision. This project aims to examine the steps taken by the visual system to code the shape of objects, including those that change shape over time. The project seeks to employ experiments assessing human vision and machine learning techniques to examine these codes and, in particular, focus on the advantages of a system that exaggerates shape change over time. Expected outcomes include an improved shape code based on superior human ....Using shape change for object perception: human and artificial vision. This project aims to examine the steps taken by the visual system to code the shape of objects, including those that change shape over time. The project seeks to employ experiments assessing human vision and machine learning techniques to examine these codes and, in particular, focus on the advantages of a system that exaggerates shape change over time. Expected outcomes include an improved shape code based on superior human performance that can have many applications in automated visual systems. This project can directly benefit the animation industries where the creation of realistic movement of humans and animals remains a computationally intensive challenge.Read moreRead less
Shape4D: Modelling the Spatiotemporal Deformation Patterns in 3D Shapes. This research will develop new mathematical methods and algorithms that will enable the use of population-level longitudinal studies to model the spatial and temporal deformation patterns in 3D biological objects. Using novel geometric and deep learning techniques, it will create new methods that will allow the characterization of how the 3D shape of objects deforms with ageing, disease progression and interaction with thei ....Shape4D: Modelling the Spatiotemporal Deformation Patterns in 3D Shapes. This research will develop new mathematical methods and algorithms that will enable the use of population-level longitudinal studies to model the spatial and temporal deformation patterns in 3D biological objects. Using novel geometric and deep learning techniques, it will create new methods that will allow the characterization of how the 3D shape of objects deforms with ageing, disease progression and interaction with their environment, and the simulation of spatiotemporal deformations in anatomical organs. Benefits include a better understanding of growth processes, predictive models of how degenerative diseases progress and a computational framework that will assist in designing proper mitigation and intervention strategies.Read moreRead less
Surviving the data deluge: Scalable feature extraction, discrimination and analysis for computer vision tasks using compressed sensed data. Strategically, our pioneering solutions besides being technically and socially significant, open fresh options for sensor-agnostic data analysis. The technical significance lies through the creation of new technologies for the critical national and global security markets, currently overwhelmed by data. The social significance arises from our solutions being ....Surviving the data deluge: Scalable feature extraction, discrimination and analysis for computer vision tasks using compressed sensed data. Strategically, our pioneering solutions besides being technically and socially significant, open fresh options for sensor-agnostic data analysis. The technical significance lies through the creation of new technologies for the critical national and global security markets, currently overwhelmed by data. The social significance arises from our solutions being privacy preserving, providing new avenues for the production of novel, socially acceptable products for aged care monitoring. Our methods spearhead future advancement in diverse disciplines due to the wide applicability of the methods to other sensor networks (Square Kilometre Array) and data types, providing new frameworks for addressing crucial problems of data management. Read moreRead less
Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an ....Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an open-source tool that can capture precision correlations between deep code features and diverse vulnerabilities to pinpoint emerging vulnerabilities without the need for bug specifications. Significant benefits include greatly improved quality, reliability and security for modern software systems.Read moreRead less
Expanding the Foundation of Planetary Science. Our understanding of the Solar System is based on a foundation of meteorite analyses. Knowing their orbital origin provides a critical spatial context, but we have this data for <0.1% of samples. This project aims to address this issue. There are 66 meteorite falls across Australia with orbits determined by the Desert Fireball Network that await recovery - more than the current global dataset. This project expects to generate new knowledge by applyi ....Expanding the Foundation of Planetary Science. Our understanding of the Solar System is based on a foundation of meteorite analyses. Knowing their orbital origin provides a critical spatial context, but we have this data for <0.1% of samples. This project aims to address this issue. There are 66 meteorite falls across Australia with orbits determined by the Desert Fireball Network that await recovery - more than the current global dataset. This project expects to generate new knowledge by applying an innovative search methodology using drones and machine learning. Expected outcomes include dramatically increasing the number of orbital meteorites. This should provide significant benefits. By linking meteorites to their parent asteroids every rock becomes a small sample-return mission.Read moreRead less
Taming media for the masses: Computational frameworks for intelligent digital media capture, management, and sharing. The core issues tackled in this project are learning, recognition and application of semantics in multimedia data and the context of its creation and use - a foundational issue in pattern recognition with many applications. The project is part of the Institute for Multi-sensor Processing and Content Analysis whose aim is to tackle technical issues in large scale pattern recogniti ....Taming media for the masses: Computational frameworks for intelligent digital media capture, management, and sharing. The core issues tackled in this project are learning, recognition and application of semantics in multimedia data and the context of its creation and use - a foundational issue in pattern recognition with many applications. The project is part of the Institute for Multi-sensor Processing and Content Analysis whose aim is to tackle technical issues in large scale pattern recognition. By developing scalable and robust techniques to extract information from large scale multi-modal data, the applications include large scale surveillance systems from multi-modal data (e.g. airport security, smart homes for the aged), context-aware devices, and the next generation of media creation and repurposing tools - a fast-growing sector of the economy.Read moreRead less
Bridging the semantic gap for building effective content management systems: Computational media aesthetics. This project focuses on video abstraction and aims to bridge the semantic gap between the simplicity of available visual features and the richness of user descriptions. We examine how visual and aural techniques are brought together to influence the engagement of audience in a story portrayal. The major outcome will be a computational framework for extracting the semantics associated wi ....Bridging the semantic gap for building effective content management systems: Computational media aesthetics. This project focuses on video abstraction and aims to bridge the semantic gap between the simplicity of available visual features and the richness of user descriptions. We examine how visual and aural techniques are brought together to influence the engagement of audience in a story portrayal. The major outcome will be a computational framework for extracting the semantics associated with audiovisual elements in television/film, and scalable software tools that can rapidly and consistently analyse media along various aesthetic dimensions. It will allow for high-level annotation of media and the building of more effective content management systems with enhanced user querying capabilities.Read moreRead less
Privacy-preserving Biometrics based Authentication and Security. Password based authentication systems cannot verify genuine users. Biometric authentication can address this issue. However, the booming IoT applications and cloud computing require that the biometric authentication must be conducted in the privacy-protected setting in order to comply with privacy protection legal regulations. Latest reports show that current biometric authentication systems, under protected setting, exhibit poor ....Privacy-preserving Biometrics based Authentication and Security. Password based authentication systems cannot verify genuine users. Biometric authentication can address this issue. However, the booming IoT applications and cloud computing require that the biometric authentication must be conducted in the privacy-protected setting in order to comply with privacy protection legal regulations. Latest reports show that current biometric authentication systems, under protected setting, exhibit poor authentication performance, which is not commercially applicable. This project aims to investigate innovative solutions to this issue. The intended deliverables will include deep learning based biometric feature extractor, cancellable biometrics and cloud oriented biometrics security protocols. Read moreRead less
Advancing the visualisation and quantification of nephrons with MRI. . This project aims to characterise key components of nephrons, the glomeruli and tubules, using magnetic resonance imaging without contrast agents, in combination with Deep Learning and super-resolution techniques. Nephrons, the basic functional unit of the kidney, are critical to the maintenance of the body’s homeostasis. Their number and architecture are critical determinants of kidney function. The expected outcomes are inn ....Advancing the visualisation and quantification of nephrons with MRI. . This project aims to characterise key components of nephrons, the glomeruli and tubules, using magnetic resonance imaging without contrast agents, in combination with Deep Learning and super-resolution techniques. Nephrons, the basic functional unit of the kidney, are critical to the maintenance of the body’s homeostasis. Their number and architecture are critical determinants of kidney function. The expected outcomes are innovative semi-automated nephron visualisation and quantitation tools that enable efficient renal phenotyping. Techniques tailored to widely accessible preclinical research scanners are expected to accelerate research into genetic and environmental factors affecting kidney microstructure in embryonic and post-natal life.Read moreRead less
Provable elimination of information leakage through timing channels. This project aims to develop techniques to solve the issue in information security of unauthorised information flow resulting from competition for shared hardware resources. The project will combine operating systems design, formal hardware models, information-flow reasoning and theorem proving to achieve a goal that is widely considered infeasible. The project is expected to result in a system that prevents leakage of critical ....Provable elimination of information leakage through timing channels. This project aims to develop techniques to solve the issue in information security of unauthorised information flow resulting from competition for shared hardware resources. The project will combine operating systems design, formal hardware models, information-flow reasoning and theorem proving to achieve a goal that is widely considered infeasible. The project is expected to result in a system that prevents leakage of critical information, such as encryption keys, through timing channels. This should prevent sophisticated attacks on public clouds, mobile devices and military-grade cross-domain devices.Read moreRead less