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Research Topic : Vision
Scheme : Discovery Projects
Field of Research : Pattern Recognition
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  • Researchers (25)
  • Funded Activities (15)
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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: 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

    Discovery Projects - Grant ID: DP0211748

    Funder
    Australian Research Council
    Funding Amount
    $276,000.00
    Summary
    Bridging the semantic gap for building effective content management systems: Computational media aesthetics. This project focuses on video abstraction and aims to bridge the semantic gap between the simplicity of available visual features and the richness of user descriptions. We examine how visual and aural techniques are brought together to influence the engagement of audience in a story portrayal. The major outcome will be a computational framework for extracting the semantics associated wi .... Bridging the semantic gap for building effective content management systems: Computational media aesthetics. This project focuses on video abstraction and aims to bridge the semantic gap between the simplicity of available visual features and the richness of user descriptions. We examine how visual and aural techniques are brought together to influence the engagement of audience in a story portrayal. The major outcome will be a computational framework for extracting the semantics associated with audiovisual elements in television/film, and scalable software tools that can rapidly and consistently analyse media along various aesthetic dimensions. It will allow for high-level annotation of media and the building of more effective content management systems with enhanced user querying capabilities.
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    Funded Activity

    Discovery Projects - Grant ID: DP0450997

    Funder
    Australian Research Council
    Funding Amount
    $180,000.00
    Summary
    Methodologies for face recognition under varying imaging conditions. Face recognition systems are heavily dependent on the nature of the input to the system. Variability in appearance due to changes in illumination, expression, pose, etc. can reduce the recognition results of the existing systems. The aim of this project is to develop new techniques to improve the recognition accuracy in natural environment where unwanted image variations exist. The development of such techniques will be of grea .... Methodologies for face recognition under varying imaging conditions. Face recognition systems are heavily dependent on the nature of the input to the system. Variability in appearance due to changes in illumination, expression, pose, etc. can reduce the recognition results of the existing systems. The aim of this project is to develop new techniques to improve the recognition accuracy in natural environment where unwanted image variations exist. The development of such techniques will be of great importance to Australia's security and safety. The outcome of this research will provide the first steps towards formulating the next generation recognition systems that will improve the suitability of the face recognition for use in security, surveillance, intelligent robotics, banking, and smart environments.
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    Funded Activity

    Discovery Projects - Grant ID: DP0664228

    Funder
    Australian Research Council
    Funding Amount
    $356,000.00
    Summary
    Unified Representations of Multimodal Biometrics for Robust Authentication and Identification. We propose two biometric systems based on two novel unified multimodal biometric representations. These systems will have a great potential impact on the national economy by reducing frauds related to identity, credit card transactions, and ATM withdrawals. Statistics show that these types of frauds are dramatically increasing in the U.S.A., the U.K., and Australia. Our systems will also have governmen .... Unified Representations of Multimodal Biometrics for Robust Authentication and Identification. We propose two biometric systems based on two novel unified multimodal biometric representations. These systems will have a great potential impact on the national economy by reducing frauds related to identity, credit card transactions, and ATM withdrawals. Statistics show that these types of frauds are dramatically increasing in the U.S.A., the U.K., and Australia. Our systems will also have government applications and will impact on the national security in areas related to immigration, passport and driver's license controls. Forensic applications include criminal identification, crime scene investigation and corpse identification (as in the case of the victims of the Asian tsunami 2004).
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    Funded Activity

    Discovery Projects - Grant ID: DP0987387

    Funder
    Australian Research Council
    Funding Amount
    $235,000.00
    Summary
    Automatic Recognition of Human Activities in Surveillance Videos: Overcoming the Curse of Dimensionality. This project will deliver a technology capable of automatically recognising human activities of interest in surveillance videos. The project will tackle the challenging, huge complexity inherent in the recognition of human activities by novel statistical pattern recognition techniques. The outcome of this project will be an effective activity recognition technology that will help monitor the .... Automatic Recognition of Human Activities in Surveillance Videos: Overcoming the Curse of Dimensionality. This project will deliver a technology capable of automatically recognising human activities of interest in surveillance videos. The project will tackle the challenging, huge complexity inherent in the recognition of human activities by novel statistical pattern recognition techniques. The outcome of this project will be an effective activity recognition technology that will help monitor the security and safety of environments and support the further development of the Australian video surveillance industry.
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    Funded Activity

    Discovery Projects - Grant ID: DP0877929

    Funder
    Australian Research Council
    Funding Amount
    $196,000.00
    Summary
    Feature-Level Fusion with Incomplete Data for Automatic Person Identification. This research addresses the current key problems in automated person recognition with incomplete data using multiple traits. The outcomes of this research will not only make a significant contribution to fundamental theory but also result in a wide range of crime and terrorism preventing applications including police database searching, access control, security monitoring and surveillance. They can be used either by p .... Feature-Level Fusion with Incomplete Data for Automatic Person Identification. This research addresses the current key problems in automated person recognition with incomplete data using multiple traits. The outcomes of this research will not only make a significant contribution to fundamental theory but also result in a wide range of crime and terrorism preventing applications including police database searching, access control, security monitoring and surveillance. They can be used either by police and law enforcement agencies, or at places of airport, government buildings, military facilities and even sensitive areas in offices and factories. It will help reduce crime, enhance the security of the nation to a world-advanced level, and generate new industry and export opportunities for Australian security industry.
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    Funded Activity

    Discovery Projects - Grant ID: DP0774118

    Funder
    Australian Research Council
    Funding Amount
    $231,090.00
    Summary
    Spectral Mutli-camera Tracking. This proposal falls well within the Research Priorities: ``Frontier Technologies for Building and Transforming Australian Industries'' and ``Safegaurding Australia''. This project, will have a direct impact in the capabilities of Australian industries to develop and implement new, leading edge technology in ICT and sensing. The technology developed throughout this project can be used to protect Australia, not only from terrorism and crime, but also from pests and .... Spectral Mutli-camera Tracking. This proposal falls well within the Research Priorities: ``Frontier Technologies for Building and Transforming Australian Industries'' and ``Safegaurding Australia''. This project, will have a direct impact in the capabilities of Australian industries to develop and implement new, leading edge technology in ICT and sensing. The technology developed throughout this project can be used to protect Australia, not only from terrorism and crime, but also from pests and diseases. The potential for biosecurity applications is a great advantage of spectral imaging and makes of this project an opportunity to track not only persons but also detect pests and diseases at strategic entry points throughout Australia, such as ports and airports.
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    Funded Activity

    Discovery Projects - Grant ID: DP0451091

    Funder
    Australian Research Council
    Funding Amount
    $165,000.00
    Summary
    Face recognition under varying pose and lighting--towards automatic personal identification for surveillance systems. One of the key remaining problems in computerized human face recognition is the need to handle the variability in appearance due to changes in pose. This proposed research targets at identifying a person with a face image in a pose different from the example view by using a novel texture analysis and synthesis technique. This technique makes use of facial textures at different vi .... Face recognition under varying pose and lighting--towards automatic personal identification for surveillance systems. One of the key remaining problems in computerized human face recognition is the need to handle the variability in appearance due to changes in pose. This proposed research targets at identifying a person with a face image in a pose different from the example view by using a novel texture analysis and synthesis technique. This technique makes use of facial textures at different viewing directions and can recover appropriate textures for virtual views in arbitrary poses. The successfulness of the proposed research would make a technical breakthrough towards solving the major remaining problem in face recognition.
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