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Field of Research : Pattern Recognition
Field of Research : Computer Vision
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  • Researchers (20)
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  • Funded Activity

    Discovery Projects - Grant ID: DP0771132

    Funder
    Australian Research Council
    Funding Amount
    $360,000.00
    Summary
    Taming media for the masses: Computational frameworks for intelligent digital media capture, management, and sharing. The core issues tackled in this project are learning, recognition and application of semantics in multimedia data and the context of its creation and use - a foundational issue in pattern recognition with many applications. The project is part of the Institute for Multi-sensor Processing and Content Analysis whose aim is to tackle technical issues in large scale pattern recogniti .... Taming media for the masses: Computational frameworks for intelligent digital media capture, management, and sharing. The core issues tackled in this project are learning, recognition and application of semantics in multimedia data and the context of its creation and use - a foundational issue in pattern recognition with many applications. The project is part of the Institute for Multi-sensor Processing and Content Analysis whose aim is to tackle technical issues in large scale pattern recognition. By developing scalable and robust techniques to extract information from large scale multi-modal data, the applications include large scale surveillance systems from multi-modal data (e.g. airport security, smart homes for the aged), context-aware devices, and the next generation of media creation and repurposing tools - a fast-growing sector of the economy.
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    Funded Activity

    Discovery Projects - Grant ID: DP0451666

    Funder
    Australian Research Council
    Funding Amount
    $150,000.00
    Summary
    A Novel System for Surveillance of Moving Objects. Surveillance of moving objects is critical in numerous applications such as detection and recognition of motor vehicles. It is important for detection to be fast and accurate with low cost. In this project, we aim to implement a surveillance system consisting of an efficient algorithm on a PC network with a camera. Our detection algorithm will be achieved with an advanced and computationally powerful image representation for fast computation. It .... A Novel System for Surveillance of Moving Objects. Surveillance of moving objects is critical in numerous applications such as detection and recognition of motor vehicles. It is important for detection to be fast and accurate with low cost. In this project, we aim to implement a surveillance system consisting of an efficient algorithm on a PC network with a camera. Our detection algorithm will be achieved with an advanced and computationally powerful image representation for fast computation. Its accuracy will be enhanced by adapting a well recognized theory for fast removal of image noise. Our implementation on the PC network will provide a flexible and extensible platform for parallel computing to further reduce detection time while keeping costs low.
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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: 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

    Linkage Projects - Grant ID: LP0668325

    Funder
    Australian Research Council
    Funding Amount
    $354,000.00
    Summary
    Automatic real-time detection of infiltrated objects for security of airports and train stations. Infiltrated objects represent a very high security threat in critical areas such as airports and train stations. In order to neutralise such a threat, this project will develop new automatic technologies capable of detecting infiltrated objects in sensitive areas in real time, analysing the movements of their original carriers in the nearby areas, and raising attention accordingly. The technologies .... Automatic real-time detection of infiltrated objects for security of airports and train stations. Infiltrated objects represent a very high security threat in critical areas such as airports and train stations. In order to neutralise such a threat, this project will develop new automatic technologies capable of detecting infiltrated objects in sensitive areas in real time, analysing the movements of their original carriers in the nearby areas, and raising attention accordingly. The technologies will be based on the automatic analysis of camera videos made by computers without the need for assessing or storing the identities of common passers-by. The potential of application is huge extending beyond airports and train stations to any public areas.
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    Funded Activity

    Discovery Projects - Grant ID: DP1093233

    Funder
    Australian Research Council
    Funding Amount
    $310,000.00
    Summary
    Surviving the data deluge: Scalable feature extraction, discrimination and analysis for computer vision tasks using compressed sensed data. Strategically, our pioneering solutions besides being technically and socially significant, open fresh options for sensor-agnostic data analysis. The technical significance lies through the creation of new technologies for the critical national and global security markets, currently overwhelmed by data. The social significance arises from our solutions being .... Surviving the data deluge: Scalable feature extraction, discrimination and analysis for computer vision tasks using compressed sensed data. Strategically, our pioneering solutions besides being technically and socially significant, open fresh options for sensor-agnostic data analysis. The technical significance lies through the creation of new technologies for the critical national and global security markets, currently overwhelmed by data. The social significance arises from our solutions being privacy preserving, providing new avenues for the production of novel, socially acceptable products for aged care monitoring. Our methods spearhead future advancement in diverse disciplines due to the wide applicability of the methods to other sensor networks (Square Kilometre Array) and data types, providing new frameworks for addressing crucial problems of data management.
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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

    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

    Linkage Projects - Grant ID: LP0883359

    Funder
    Australian Research Council
    Funding Amount
    $483,400.00
    Summary
    Smart technologies for people with vision impairment and blindness. Our technological solutions for early detection of disease provide the best opportunity for effective treatment, and provision of strategies capable of assisting individuals. It aims to empower primary care providers and will lead to more effective screening methods and improved efficiencies in redirecting resources towards those whose eye disease is treatable. It will further improve and enable access to specialist eye care fo .... Smart technologies for people with vision impairment and blindness. Our technological solutions for early detection of disease provide the best opportunity for effective treatment, and provision of strategies capable of assisting individuals. It aims to empower primary care providers and will lead to more effective screening methods and improved efficiencies in redirecting resources towards those whose eye disease is treatable. It will further improve and enable access to specialist eye care for those living in rural, regional and remote locations. The assistive technologies for the blind will greatly enhance the quality of life of the visually impaired, enhancing their quality of life and removing several risk factors. The net annual savings to the Government from these projects would be considerable.
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    Funded Activity

    Linkage Projects - Grant ID: LP0560847

    Funder
    Australian Research Council
    Funding Amount
    $72,444.00
    Summary
    Fruit shape estimation from stereoscopic images in real time. The research aims at improving the process of automatic fruit inspection and classification. Existing stereo vision algorithms to extract depth information are unsuitable for real time calculations. The increasing complexity and reducing cost of field programmable gate arrays along with the development of algorithms that have a high degree of parallelism and locality has created the possibility of performing the calculation .... Fruit shape estimation from stereoscopic images in real time. The research aims at improving the process of automatic fruit inspection and classification. Existing stereo vision algorithms to extract depth information are unsuitable for real time calculations. The increasing complexity and reducing cost of field programmable gate arrays along with the development of algorithms that have a high degree of parallelism and locality has created the possibility of performing the calculations required in real time. This projects aims to investigate the suitability of the various stereo vision algorithms available in the literature for real time hardware implementation with application to fruit shape estimation it real time.
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