Feature Detection and Computer-aided Diagnosis with Longitudinal Tracking of Benign Asbestos-Related Pleural Disease in CT images. This project seeks to develop smart and novel feature extraction and knowledge acquisition techniques to assist radiologists in automated diagnosis and assessment of lung diseases. These outcomes will lead to improved delivery of health services in Australia, including in rural regions. They will lead to more accurate assessment of asbestos related pleural diseases f ....Feature Detection and Computer-aided Diagnosis with Longitudinal Tracking of Benign Asbestos-Related Pleural Disease in CT images. This project seeks to develop smart and novel feature extraction and knowledge acquisition techniques to assist radiologists in automated diagnosis and assessment of lung diseases. These outcomes will lead to improved delivery of health services in Australia, including in rural regions. They will lead to more accurate assessment of asbestos related pleural diseases for compensation and treatment and better followup, leading to earlier treatment and better quality of life for patients suffering from lung diseases. The project will also save costs due to automated assessment as well as the potential for fewer patient scans.Read moreRead less
Semantic Vectorisation: From Bitmaps to Intelligent Representations. The objective of this innovative project is to provide a solution to the open question of representing natural images by semantically rich vector graphics. The challenges are to identify key visual and temporal elements for images and videos, and efficiently decompose the visual data into semantic vector representations that are faithful to original data, compact and editable. The project aims to investigate new bitmap-to-vecto ....Semantic Vectorisation: From Bitmaps to Intelligent Representations. The objective of this innovative project is to provide a solution to the open question of representing natural images by semantically rich vector graphics. The challenges are to identify key visual and temporal elements for images and videos, and efficiently decompose the visual data into semantic vector representations that are faithful to original data, compact and editable. The project aims to investigate new bitmap-to-vector conversion methods. It is expected to develop a framework where semantic labels and hyperlinks can be embedded in visual data automatically. It hopes to pioneer the creation of a web of images where the links are on image/video regions. New image simplification, stylisation, and non-photorealistic rendering methods are expected to be provided.Read moreRead less
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.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE100100235
Funder
Australian Research Council
Funding Amount
$280,000.00
Summary
Accelerating Australia's large scale video surveillance research programmes. The research to be conducted using this infrastructure will bring immense benefits to Australia in terms of increased levels of public safety and in the protection of critical facilities from terrorism and other crimes, by developing better surveillance systems. This will provide both increases in measurable research outputs and opportunities for Australian business to commercialise these systems. The infrastructure wil ....Accelerating Australia's large scale video surveillance research programmes. The research to be conducted using this infrastructure will bring immense benefits to Australia in terms of increased levels of public safety and in the protection of critical facilities from terrorism and other crimes, by developing better surveillance systems. This will provide both increases in measurable research outputs and opportunities for Australian business to commercialise these systems. The infrastructure will accelerate the pace of surveillance research and development in Australia, enhancing the competitiveness of both Australia's researchers and the businesses that will commercialise these researchers' discoveries.Read moreRead less
LittleBrother: Vision Systems Supporting Detection of Offenders in Public Places. Current visual surveillance systems can track people in an area only if complete camera coverage is provided. This project will develop a visual surveillance system able to track and record people's movements in a public building requiring only limited visual coverage. We will propose novel ways of matching images of a single individual from distant cameras by using features such as color histograms decomposed for ....LittleBrother: Vision Systems Supporting Detection of Offenders in Public Places. Current visual surveillance systems can track people in an area only if complete camera coverage is provided. This project will develop a visual surveillance system able to track and record people's movements in a public building requiring only limited visual coverage. We will propose novel ways of matching images of a single individual from distant cameras by using features such as color histograms decomposed for the different body parts, estimated height, and build type. Creating a record with this tracking information will effectively support security officers in the identification of responsible parties in the event of an offence.Read moreRead less
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.Read moreRead less
A general Bayesian multilinear analysis framework for human behaviour recognition. Smart information use is essential for effective video surveillance in order to guard against accidents, fight crime and combat terrorism. In this project advanced probabilistic methods will be applied to visual surveillance information, to warn of impending accidents and to track criminals and terrorists and predict their behaviours.
Discovery Early Career Researcher Award - Grant ID: DE180101438
Funder
Australian Research Council
Funding Amount
$356,446.00
Summary
Multi-view synergistic learning for human behaviour analysis. This project aims to equip machines with a human-likeability to synergistically harness multiple information sources for the purpose of optimal decision-making. This project will produce the next great step for machine intelligence - laying the theoretical foundation for the learning of multiple views and building the next generation of intelligent systems which can accommodate multiple information sources. This research is fundament ....Multi-view synergistic learning for human behaviour analysis. This project aims to equip machines with a human-likeability to synergistically harness multiple information sources for the purpose of optimal decision-making. This project will produce the next great step for machine intelligence - laying the theoretical foundation for the learning of multiple views and building the next generation of intelligent systems which can accommodate multiple information sources. This research is fundamental to the creation of intelligent systems that elegantly tackle varieties of big data. This should benefit science, society, and the economy nationally through applications including autonomous vehicle development, sensor technologies, and human behaviour analysis.Read moreRead less
A theoretical framework for practical partial fingerprint identification. Fingerprints captured from a crime scene are often partial and poor quality which makes it difficult to identify the criminal suspects from large databases. This project will find mathematical models which can estimate the missing information located in the blank areas of a partial fingerprint and effectively identify it.