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Socio-Economic Objective : Information processing services
Research Topic : Visual Function
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  • Funded Activity

    Discovery Projects - Grant ID: DP0346475

    Funder
    Australian Research Council
    Funding Amount
    $218,720.00
    Summary
    A Computer-Aided Cartooning System. This project is aimed at developing a computer-aided system to accelerate main image-related processes in cartoon production. Using such a system, many of the tedious and repetitive tasks can be performed semi-automatically. The project is focused on accurate representation and matching of shapes. New vectorization methods based on projection onto convex sets (POCS), and new matching methods based on multi-stage hierarchical structures will be developed. The t .... A Computer-Aided Cartooning System. This project is aimed at developing a computer-aided system to accelerate main image-related processes in cartoon production. Using such a system, many of the tedious and repetitive tasks can be performed semi-automatically. The project is focused on accurate representation and matching of shapes. New vectorization methods based on projection onto convex sets (POCS), and new matching methods based on multi-stage hierarchical structures will be developed. The targeted applications include entertainment, next generation mobile services, and the internet.
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    Funded Activity

    Discovery Projects - Grant ID: DP0558979

    Funder
    Australian Research Council
    Funding Amount
    $158,000.00
    Summary
    Detecting, Locating and Tracking Human Faces using Skin Colour. With growing concerns for national security and public safety, government agencies in Australia and around the world are taking strong measures to introduce biometric-enhanced official identification documents such as passports, visas, and ID cards. The proposed face detection and tracking system will play a key role in personal identification and human activity monitoring. The developed system will have a huge potential in surveill .... Detecting, Locating and Tracking Human Faces using Skin Colour. With growing concerns for national security and public safety, government agencies in Australia and around the world are taking strong measures to introduce biometric-enhanced official identification documents such as passports, visas, and ID cards. The proposed face detection and tracking system will play a key role in personal identification and human activity monitoring. The developed system will have a huge potential in surveillance, security, law enforcement, and ICT. This project will contribute to building a knowledge economy in Australia and help safeguard and protect Australia from terrorism and crime. Furthermore, its outcomes will enhance the reputation of Australia as a leader in frontier technologies and smart information use.
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    Funded Activity

    Discovery Projects - Grant ID: DP0343610

    Funder
    Australian Research Council
    Funding Amount
    $277,440.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP0773761

    Funder
    Australian Research Council
    Funding Amount
    $255,000.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP0881706

    Funder
    Australian Research Council
    Funding Amount
    $304,322.00
    Summary
    Algorithmics for Interactive 2.5D Graph Drawing. Technological advances have provided a data deluge over the past few years, and consequently have led to many large and complex network models in many domains. This includes terrorrist networks and biological networks, software engineering structures, and webgraphs. Visualisation is an effective tool in helping humans to understand such networks. This project aims to provide a new direction in network visualisation, using 2.5 dimensions. The algor .... Algorithmics for Interactive 2.5D Graph Drawing. Technological advances have provided a data deluge over the past few years, and consequently have led to many large and complex network models in many domains. This includes terrorrist networks and biological networks, software engineering structures, and webgraphs. Visualisation is an effective tool in helping humans to understand such networks. This project aims to provide a new direction in network visualisation, using 2.5 dimensions. The algorithms developed in the project will help security analysts to detect abnormal behavious such as money laundering, help biologists understand protein-protein interaction networks, and help engineers to understand large software systems.
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    Funded Activity

    Linkage Projects - Grant ID: LP0991757

    Funder
    Australian Research Council
    Funding Amount
    $240,000.00
    Summary
    Generic Content-based News Picture Retrieval with Local Invariant Features. Image Retrieval searches for images from large databases whose visual content meets the requirements submitted by users. Besides directly benefiting the Partner Organization, this project will enable more efficient access to large picture repositories in news agencies and publishers, digital libraries and film archives. It will make public use of visual information much more convenient and economical. It will help securi .... Generic Content-based News Picture Retrieval with Local Invariant Features. Image Retrieval searches for images from large databases whose visual content meets the requirements submitted by users. Besides directly benefiting the Partner Organization, this project will enable more efficient access to large picture repositories in news agencies and publishers, digital libraries and film archives. It will make public use of visual information much more convenient and economical. It will help security officers to effortlessly and accurately find particular scenes from the images generated by a large closed-circuit TV networks. Also, the developed technology can be applied to tele-education and e-commerce. New algorithms developed in this project will benefit the Australian and world scientific communities.
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    Funded Activity

    Discovery Projects - Grant ID: DP0988838

    Funder
    Australian Research Council
    Funding Amount
    $263,000.00
    Summary
    Scalable Visual Analytics for Uncertain Dynamic Networks. Technological advances have provided a data deluge over the past few years, and have led to many large uncertain and dynamic network models. This includes terrorist networks, marketing networks, facebook networks, various biological networks, and software engineering structures. Human understanding of such networks is difficult. This project aims to provide new methods for visual analysis of large uncertain dynamic networks such as these. .... Scalable Visual Analytics for Uncertain Dynamic Networks. Technological advances have provided a data deluge over the past few years, and have led to many large uncertain and dynamic network models. This includes terrorist networks, marketing networks, facebook networks, various biological networks, and software engineering structures. Human understanding of such networks is difficult. This project aims to provide new methods for visual analysis of large uncertain dynamic networks such as these. The algorithms developed in the project will help security analysts to monitor illegal behaviour such as money laundering and terrorist activities, help biologists understand key biological systems, and help engineers to understand large software systems.
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    Showing 1-7 of 7 Funded Activites

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