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Scheme : Linkage Projects
Research Topic : learning
Field of Research : Computer Vision
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  • Funded Activity

    Linkage Projects - Grant ID: LP0989998

    Funder
    Australian Research Council
    Funding Amount
    $320,000.00
    Summary
    Autonomous repeatable surveys for long term monitoring of marine habitats. Australia has committed to using marine resources in a sustainable manner and to conserve the biodiversity of its marine habitats. In order to manage its marine environment effectively, marine scientists, managers and policy makers require timely and accurate information on the state of the environment. Current knowledge and techniques are limited and will have difficulty scaling to satisfy Australia's needs. A monitorin .... Autonomous repeatable surveys for long term monitoring of marine habitats. Australia has committed to using marine resources in a sustainable manner and to conserve the biodiversity of its marine habitats. In order to manage its marine environment effectively, marine scientists, managers and policy makers require timely and accurate information on the state of the environment. Current knowledge and techniques are limited and will have difficulty scaling to satisfy Australia's needs. A monitoring system that relies on machines to perform a substantial fraction of survey work and basic data analysis can scale more easily and provide more information at lower costs.
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    Funded Activity

    Linkage Projects - Grant ID: LP100200430

    Funder
    Australian Research Council
    Funding Amount
    $255,000.00
    Summary
    Design of adaptive learning visual sensor networks for crowd modelling in high-density and occluded scenarios. Partnering University of Melbourne researchers, with video surveillance experts SenSen, engineering consultants ARUP and the Melbourne Cricket Club, the project addresses research enabling a system-integrating, existing surveillance, infrastructure to model crowd behaviour and exit strategies, providing real-time analysis, prediction and response capabilities for venue managers and emer .... Design of adaptive learning visual sensor networks for crowd modelling in high-density and occluded scenarios. Partnering University of Melbourne researchers, with video surveillance experts SenSen, engineering consultants ARUP and the Melbourne Cricket Club, the project addresses research enabling a system-integrating, existing surveillance, infrastructure to model crowd behaviour and exit strategies, providing real-time analysis, prediction and response capabilities for venue managers and emergency services. This new capability enhances utilisation of security resources to prevent injury and fatalities in evacuation scenarios, applicable to existing venues and influencing the development of new facilities around the country. The project delivers researcher training, global clientele for local technology and a platform for local industry growth.
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