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Field of Research : Pattern Recognition
Field of Research : Image Processing
Australian State/Territory : VIC
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  • Funded Activity

    Discovery Projects - Grant ID: DP0666456

    Funder
    Australian Research Council
    Funding Amount
    $168,000.00
    Summary
    Pattern-Based Video Coding Techniques for Real-Time Low Bit-Rate and Low Complexity Encoding Applications. This project will benefit the National Research Priority on Frontier Technology with applications in video surveillance, smart home design, and patient monitoring. It will enable Australia to lead the world in setting up coding standards and thus impact directly on the manufacturing initiatives of the multimedia communication and entertainment industries. Telecommunication industries will b .... Pattern-Based Video Coding Techniques for Real-Time Low Bit-Rate and Low Complexity Encoding Applications. This project will benefit the National Research Priority on Frontier Technology with applications in video surveillance, smart home design, and patient monitoring. It will enable Australia to lead the world in setting up coding standards and thus impact directly on the manufacturing initiatives of the multimedia communication and entertainment industries. Telecommunication industries will be the immediate beneficiary by enabling quality live video transmissions at low bit rates in a cost-effective manner. This project will improve the ability of large organisations to operate virtually across huge distances in Australia with the aid of reliable multimedia communications using distributed devices of limited power and processing capacity.
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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

    Special Research Initiatives - Grant ID: SR0354604

    Funder
    Australian Research Council
    Funding Amount
    $10,000.00
    Summary
    ARC Network in Imaging Science and Technology. The ARC Network in Imaging Science and Technology is a field of research network covering the fundamental science and technological development of applied imaging systems. The network will encompass all aspects of the imaging sciences from image formation, through image processing and analysis, and on to image visualisation. In particular, the network will focus on a number of application areas that utilise these core technologies: medical imaging; .... ARC Network in Imaging Science and Technology. The ARC Network in Imaging Science and Technology is a field of research network covering the fundamental science and technological development of applied imaging systems. The network will encompass all aspects of the imaging sciences from image formation, through image processing and analysis, and on to image visualisation. In particular, the network will focus on a number of application areas that utilise these core technologies: medical imaging; surveillance and security; materials science and metallurgy; environmental monitoring; and consumer imaging. In this way, the network will provide an environment for creative inter-disciplinary research to the socio-economic benefit of Australia.
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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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    Funded Activity

    Linkage Projects - Grant ID: LP0348883

    Funder
    Australian Research Council
    Funding Amount
    $151,507.00
    Summary
    Non-Contact In-process Shape Measurement of Windscreens. Optical techniques have been widely used for non-contact measurement of the 3-D shape of diffusely reflecting surfaces. However, there is no evidence for the successful implementation of a real-time shape measurement system for large specular surfaces, despite the many important industrial applications. The aim of this project is to develop optically-based techniques to measure the shape of specular and transparent surfaces in real time in .... Non-Contact In-process Shape Measurement of Windscreens. Optical techniques have been widely used for non-contact measurement of the 3-D shape of diffusely reflecting surfaces. However, there is no evidence for the successful implementation of a real-time shape measurement system for large specular surfaces, despite the many important industrial applications. The aim of this project is to develop optically-based techniques to measure the shape of specular and transparent surfaces in real time in an industrial environment. The main outcome of the research will be a prototype on-line shape measurement system to control the quality of car windscreens.
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    Funded Activity

    Linkage Projects - Grant ID: LP0455257

    Funder
    Australian Research Council
    Funding Amount
    $70,668.00
    Summary
    Robust face detection and recognition for computer-based security surveillance. The research aims at improving the existing and creating new automated face detection and recognition methods by making them invariant, firstly to head pose, orientation, scale and rotation, and then to occlusion, lighting conditions and facial expressions. A robust face detector will be developed first and then a new face recognition algorithm that continues to learn identity-specific discriminants on-line by co .... Robust face detection and recognition for computer-based security surveillance. The research aims at improving the existing and creating new automated face detection and recognition methods by making them invariant, firstly to head pose, orientation, scale and rotation, and then to occlusion, lighting conditions and facial expressions. A robust face detector will be developed first and then a new face recognition algorithm that continues to learn identity-specific discriminants on-line by collecting incremental face exemplars. The result of the research will be an algorithm that can improve its performance on-line adapting in a stable learning process each identity model to the correct facial examples. The research has significant practical implication in visual surveillance increasing the robustness of identification of person identity, state and intent.
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    Funded Activity

    Discovery Projects - Grant ID: DP0985838

    Funder
    Australian Research Council
    Funding Amount
    $247,000.00
    Summary
    Developing Reliable Bio-Crypto Features for Mobile Template Protection. Cost of identity theft crimes were at multi-million dollars in Australia in 2007. Technically this is due to the fact that conventional personal identification number and token based security mechanisms cannot identify genuine users. Biometric fingerprint security systems emerge as a promising solution. However protection of the mobile embedded fingerprint template itself is an unresolved problem. The project aims to devel .... Developing Reliable Bio-Crypto Features for Mobile Template Protection. Cost of identity theft crimes were at multi-million dollars in Australia in 2007. Technically this is due to the fact that conventional personal identification number and token based security mechanisms cannot identify genuine users. Biometric fingerprint security systems emerge as a promising solution. However protection of the mobile embedded fingerprint template itself is an unresolved problem. The project aims to develop new ways designing bio-cryptosystems that provide strong security strength. The project will bring new body of knowledge into this field and place Australia in the forefront of this research, and also result in strengthened security of IT infrastructure and systems for industries.
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    Funded Activity

    Linkage Projects - Grant ID: LP0347069

    Funder
    Australian Research Council
    Funding Amount
    $69,099.00
    Summary
    Methodologies for automatic visual identification in heat detection aids. New techniques will be designed and developed to automate the existing manual heat detection of cattle, under general imaging conditions. The proposed intelligent system will consist of six stages: 1- image acquisition, 2- image preprocessing, 3- presence detection, 4- illumination compensation, 5- HD detection, and 6- heat detection. The proposed system will handle various image variations, and will be fast and cost-effec .... Methodologies for automatic visual identification in heat detection aids. New techniques will be designed and developed to automate the existing manual heat detection of cattle, under general imaging conditions. The proposed intelligent system will consist of six stages: 1- image acquisition, 2- image preprocessing, 3- presence detection, 4- illumination compensation, 5- HD detection, and 6- heat detection. The proposed system will handle various image variations, and will be fast and cost-effective. The developed system will improve the productivity of Australian cattle industry.
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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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