Advancing Medical Image Analysis through High Performance Heterogeneous Computing, Numerical Simulation, and Novel Human Computer Interfaces. This project will link Australian researchers with a major multi-national IT company. The engagement of world-class personnel from Microsoft will provide unprecedented opportunities for graduate students to experience research in both an academic and an industrial setting. The participation of Microsoft product division offers the potential to transform th ....Advancing Medical Image Analysis through High Performance Heterogeneous Computing, Numerical Simulation, and Novel Human Computer Interfaces. This project will link Australian researchers with a major multi-national IT company. The engagement of world-class personnel from Microsoft will provide unprecedented opportunities for graduate students to experience research in both an academic and an industrial setting. The participation of Microsoft product division offers the potential to transform the outcomes of this project into widely-used software solutions. The project will pave the way for more widespread and reliable evidenced-based computer-aided diagnosis and image-guided treatment. It will produce well-trained and sought-after graduates and research associates with extensive inter-disciplinary knowledge of medical image analysis and high-performance computing.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120102960
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Revocable multi-dimensional shape-based multimodal hand biometrics for personal identification and verification. This project will investigate a new personal verification system based on hand biometrics. It will make significant improvements by thwarting identity frauds; creating trust in ebanking and epayments; providing social acceptance of biometrics; helping immigration and passport control; and reducing use of plastic cards to safeguard the environment.
Discovery Early Career Researcher Award - Grant ID: DE220101379
Funder
Australian Research Council
Funding Amount
$417,000.00
Summary
Towards Transferable Visual Understanding in the Real World. This project aims to investigate how to improve the transferability of visual understanding algorithm and system in the real-world applications. This project expects to innovate and advance knowledge in the fields of visual transfer learning and generalizable visual representation learning. Expected outcomes of this project include techniques and algorithms to make the visual understanding system robust to diverse real-world scenarios. ....Towards Transferable Visual Understanding in the Real World. This project aims to investigate how to improve the transferability of visual understanding algorithm and system in the real-world applications. This project expects to innovate and advance knowledge in the fields of visual transfer learning and generalizable visual representation learning. Expected outcomes of this project include techniques and algorithms to make the visual understanding system robust to diverse real-world scenarios. This project should provide significant benefits, such as improving the robustness and safety of autonomous vehicles in transportation area, and reducing the cost of destructive data collection for intelligent fault detection in advanced manufacturing area.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140100180
Funder
Australian Research Council
Funding Amount
$394,305.00
Summary
Advancing Dense 3D Reconstruction of Non-rigid Scenes by Using a Moving Camera. This project will advance the fundamental research in geometric computer vision and develop a new framework for efficient dense three-dimensional reconstruction of non-rigid scenes by using a moving camera. It is expected that this project will bring about breakthroughs in geometric computer vision with many daily applications, including three-dimensional natural human-computer interaction, three-dimensional reconstr ....Advancing Dense 3D Reconstruction of Non-rigid Scenes by Using a Moving Camera. This project will advance the fundamental research in geometric computer vision and develop a new framework for efficient dense three-dimensional reconstruction of non-rigid scenes by using a moving camera. It is expected that this project will bring about breakthroughs in geometric computer vision with many daily applications, including three-dimensional natural human-computer interaction, three-dimensional reconstruction from historical movies and three-dimensional realistic animations. Its outcomes will enable users to capture and manipulate their surrounding dynamic world in three-dimensions easily and conveniently. This project will alleviate many of the major difficulties (dense correspondences, long sequences, complex deformations) with conventional non-rigid reconstruction methods.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
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
Automated Determination of the Pose of a Human from Visual Information - Markerless 3D Pose Recovery of Humans from Videos. The development of 3D human pose recovery has been sought by computer vision researchers for many years. Our results will, firstly, have benefit for Australia's standing in the international computer vision community. Over time, the research outcomes will be developed into a software product for rehabilitation analysis by recognizing discrepancies between the walking pat ....Automated Determination of the Pose of a Human from Visual Information - Markerless 3D Pose Recovery of Humans from Videos. The development of 3D human pose recovery has been sought by computer vision researchers for many years. Our results will, firstly, have benefit for Australia's standing in the international computer vision community. Over time, the research outcomes will be developed into a software product for rehabilitation analysis by recognizing discrepancies between the walking patterns of healthy individuals and those with abnormalities as a result of accidents or diseases. The Australian economy will benefit by the reduction in the lifetime cost of injuries. This software will also provide benefits to the movie animation, computer games industry, and the training of athletes.Read moreRead less
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
An automated 3D model-based object recognition system. A novel, practical 3D vision system is proposed as a platform for fundamental applied research in 3D data acquisition, object modelling and object recognition. The significance of the vision system lies in the advancement of knowledge in three key areas of computer vision, registration, recognition and error propagation. The result is a system capable of sensing, modelling and identifying arbitrarily shaped free-form objects in a scene, an a ....An automated 3D model-based object recognition system. A novel, practical 3D vision system is proposed as a platform for fundamental applied research in 3D data acquisition, object modelling and object recognition. The significance of the vision system lies in the advancement of knowledge in three key areas of computer vision, registration, recognition and error propagation. The result is a system capable of sensing, modelling and identifying arbitrarily shaped free-form objects in a scene, an attribute lacking in current systems. Such a system can provide substantial economic benefits to industrial procedures such as grasp planning and quality control.Read moreRead less
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.