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Field of Research : Computer Vision
Field of Research : Image Processing
Research Topic : Software
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  • Researchers (19)
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  • Funded Activity

    Discovery Projects - Grant ID: DP0771294

    Funder
    Australian Research Council
    Funding Amount
    $257,000.00
    Summary
    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.
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    Funded Activity

    Linkage Projects - Grant ID: LP160100495

    Funder
    Australian Research Council
    Funding Amount
    $275,000.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP0344338

    Funder
    Australian Research Council
    Funding Amount
    $242,242.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP0878801

    Funder
    Australian Research Council
    Funding Amount
    $422,000.00
    Summary
    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.
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    Funded Activity

    Linkage Projects - Grant ID: LP130100230

    Funder
    Australian Research Council
    Funding Amount
    $260,000.00
    Summary
    Application of manifold-based image analysis to identify subtle changes in digitally-captured pathology samples. This project will research and develop advanced computer aided analytics for digital pathology with the aim of automating several common pathology tests. This project should not only greatly increase the speed of pathology tests but should also improve quality, lower costs and improve patient outcomes.
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    Funded Activity

    Linkage Projects - Grant ID: LP120100595

    Funder
    Australian Research Council
    Funding Amount
    $145,000.00
    Summary
    A theoretical framework for practical partial fingerprint identification. Fingerprints captured from a crime scene are often partial and poor quality which makes it difficult to identify the criminal suspects from large databases. This project will find mathematical models which can estimate the missing information located in the blank areas of a partial fingerprint and effectively identify it.
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    Funded Activity

    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.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE120101778

    Funder
    Australian Research Council
    Funding Amount
    $375,000.00
    Summary
    Building change detection and map update using multispectral imagery and height data. This project will produce an effective building change detection procedure and a digital building map. Automatic building detection assists in taking possible precautions during natural disasters, whilst automatic building change detection facilitates an effective and efficient management of affected areas during and after the calamity.
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    Funded Activity

    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.
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    Showing 1-9 of 9 Funded Activites

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