3D Image segmentation and shape characterisation driven by topological persistence. Tomographic imaging is emerging as a new tool to help tackle a remarkable array of scientific challenges. What distinguishes healthy bone from that of osteoporosis sufferers? How does groundwater contamination spread? Why is a macadamia nut so hard to crack? What causes the iridescence in a butterfly wing? These are just a few of the questions being answered at tomographic facilities in Australia alone. By co ....3D Image segmentation and shape characterisation driven by topological persistence. Tomographic imaging is emerging as a new tool to help tackle a remarkable array of scientific challenges. What distinguishes healthy bone from that of osteoporosis sufferers? How does groundwater contamination spread? Why is a macadamia nut so hard to crack? What causes the iridescence in a butterfly wing? These are just a few of the questions being answered at tomographic facilities in Australia alone. By combining sophisticated mathematics with cutting edge image-processing algorithms, this project will yield a new class of topology driven image analysis techniques that will improve the accuracy and reliability of predictions made from tomographic images.Read moreRead less
Leveraging 3D computer vision for camera-based precise geo-localisation. This project aims to develop advanced 3D computer vision and image processing technology that can turn regular cameras into high-precision location-sensing devices. Spatial Location is a fundamental type of information of our physical world. Determining the precise location of people, vehicle, and mobile devices is essential for many critical applications. Outcomes of the project will enable a wide range of novel applicatio ....Leveraging 3D computer vision for camera-based precise geo-localisation. This project aims to develop advanced 3D computer vision and image processing technology that can turn regular cameras into high-precision location-sensing devices. Spatial Location is a fundamental type of information of our physical world. Determining the precise location of people, vehicle, and mobile devices is essential for many critical applications. Outcomes of the project will enable a wide range of novel applications of significant social, environmental and economic value, such as Location-Aware Service, Environment Monitoring, Augmented Reality, Autonomous Vehicle, and Rapid Emergency Response. The project will enhance Australia's international competitive advantage in forefront of ICT research and technology innovation.Read moreRead less
Developing Reliable Bio-Crypto Features for Mobile Template Protection. Cost of identity theft crimes were at multi-million dollars in Australia in 2007. Technically this is due to the fact that conventional personal identification number and token based security mechanisms cannot identify genuine users. Biometric fingerprint security systems emerge as a promising solution. However protection of the mobile embedded fingerprint template itself is an unresolved problem. The project aims to devel ....Developing Reliable Bio-Crypto Features for Mobile Template Protection. Cost of identity theft crimes were at multi-million dollars in Australia in 2007. Technically this is due to the fact that conventional personal identification number and token based security mechanisms cannot identify genuine users. Biometric fingerprint security systems emerge as a promising solution. However protection of the mobile embedded fingerprint template itself is an unresolved problem. The project aims to develop new ways designing bio-cryptosystems that provide strong security strength. The project will bring new body of knowledge into this field and place Australia in the forefront of this research, and also result in strengthened security of IT infrastructure and systems for industries.Read moreRead less
Parametric VR: An Interactive Virtual Reality System for Parametric Design. This project aims to create a new and intuitive set of user interactions for Virtual Reality (VR) to support parametric designers in architecture and design. Parametric tools are an emerging design technology dominating contemporary practices, yet their interfaces are on traditional desktop computers while VR is only employed to visualise the geometric models produced by the end design. This project will generate Paramet ....Parametric VR: An Interactive Virtual Reality System for Parametric Design. This project aims to create a new and intuitive set of user interactions for Virtual Reality (VR) to support parametric designers in architecture and design. Parametric tools are an emerging design technology dominating contemporary practices, yet their interfaces are on traditional desktop computers while VR is only employed to visualise the geometric models produced by the end design. This project will generate Parametric VR, a system of VR tools to support parametric design. Key outcomes include software tools and demonstrators to support parametric algorithms and processes in VR. This will have significant benefits for design industries, allowing designers to directly edit parametric design entirely in VR across the project lifecycle.Read moreRead less
Solve it or Ignore it? The Challenge of Alignment Distortion and Creating Next Generation Automatic Facial Expression Detection. The last two decades have seen an escalating interest in automating the coding of facial expressions. Despite this keen interest, the promise of computer vision systems to accurately code facial expressions in natural circumstances remains elusive. Our interdisciplinary team will research a new paradigm to account for facial alignment distortion directly rather than ai ....Solve it or Ignore it? The Challenge of Alignment Distortion and Creating Next Generation Automatic Facial Expression Detection. The last two decades have seen an escalating interest in automating the coding of facial expressions. Despite this keen interest, the promise of computer vision systems to accurately code facial expressions in natural circumstances remains elusive. Our interdisciplinary team will research a new paradigm to account for facial alignment distortion directly rather than aiming to achieve invariance to it. The project will also research new data agnostic feature compaction capabilities to enable scalable learning on the world’s largest and challenging expression dataset available to us through international collaboration. Tackling these two major open problems will make accurate coding of facial expressions in natural environments achievable.Read moreRead less
Pattern Recognition and Scene Analysis via Machine Learning. We plan to use kernel methods, a novel machine learning technique, for computer vision problems, such as scene analysis and real time object recognition. Such capabilities are relevant for the design of intelligent and adaptive systems, suitable for complex real world environments. Expected outcomes are the design of efficient statistical tools which take the special nature of visual data into account (structure, decomposition, prior ....Pattern Recognition and Scene Analysis via Machine Learning. We plan to use kernel methods, a novel machine learning technique, for computer vision problems, such as scene analysis and real time object recognition. Such capabilities are relevant for the design of intelligent and adaptive systems, suitable for complex real world environments. Expected outcomes are the design of efficient statistical tools which take the special nature of visual data into account (structure, decomposition, prior knowledge of physical environments, etc.) and combine the advantages of feature based high-level vision methods with low-level machine learning techniques.
This proposal is part of a joint IST project with partners from the European Union.Read moreRead less
Computer Vision Optimization Problems Using Machine Learning. Computer Vision concerns itself with understanding the world through the analysis of images obtained by a video or still camera. An important application is tracking of people in video and modelling their movements. This has evident applications in security, sport and entertainment. By enabling the computer to capture the motion of a subject in a video, we may detect suspicious activity in security, analyze the motion (golf-swing, ....Computer Vision Optimization Problems Using Machine Learning. Computer Vision concerns itself with understanding the world through the analysis of images obtained by a video or still camera. An important application is tracking of people in video and modelling their movements. This has evident applications in security, sport and entertainment. By enabling the computer to capture the motion of a subject in a video, we may detect suspicious activity in security, analyze the motion (golf-swing, diving style) of a sports-person, or capture the motion of an actor for animation or game applications. Development of a reliable technology requires new optimization techniques, which will place Australia at the forefront of the application of such research, commercially and for the public benefit.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.
Hybrid optimisation for automatic large-scale video annotation. Optimization is the basis for solving many problems in Computer Vision, such as three-dimensional geometry recovery, image segmentation, scene labeling and object recognition. This project will develop new optimisation techniques and demonstrate their suitability for large-scale video annotation, which is key to visual data mining and scene understanding.
Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era. In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering ap ....Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era. In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering applications which will both reduced the bandwidth required and make the internet safer for users. Finally, it will enable rapid deployment of sensor networks for monitoring and detection, such as for environmental monitoring and safeguarding Australia's borders.Read moreRead less