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Field of Research : Image Processing
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  • Funded Activity

    Discovery Projects - Grant ID: DP0211387

    Funder
    Australian Research Council
    Funding Amount
    $222,932.00
    Summary
    Smart CMOS Vision Sensors in Deep Sub-0.25um CMOS Technologies. This research project aims to develop a new generation of smart vision sensors featuring on-chip and pixel-level implementation of human vision based algorithms. Built in state-of-the-art deep sub-0.25um CMOS technologies, these imagers will feature extensive in-pixel processing power in contrast to the currently commercially available CMOS vision sensors. This will enable on-chip vision-based decision making but also increased on-c .... Smart CMOS Vision Sensors in Deep Sub-0.25um CMOS Technologies. This research project aims to develop a new generation of smart vision sensors featuring on-chip and pixel-level implementation of human vision based algorithms. Built in state-of-the-art deep sub-0.25um CMOS technologies, these imagers will feature extensive in-pixel processing power in contrast to the currently commercially available CMOS vision sensors. This will enable on-chip vision-based decision making but also increased on-chip image processing. These innovative system-on-chip features will contribute towards the positioning of CMOS imaging technology as the technology of choice for most digital imaging applications, in place of the existing, and so far unchallenged, CCD technology.
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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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