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
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.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
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.Read moreRead less
Dynamic Visual Scene Gist Recognition using a Probabilistic Inference Framework. How can we see the forest without intentionally looking for the trees? How can we tell traffic is flowing smoothly on a busy highway without identifying vehicles or measuring their speed? These are the questions that inspire this research project. Humans are endowed with the ability to grasp the ‘gist’ or overall meaning of a complex visual scene from a single glance and without attention to details. The aim of this ....Dynamic Visual Scene Gist Recognition using a Probabilistic Inference Framework. How can we see the forest without intentionally looking for the trees? How can we tell traffic is flowing smoothly on a busy highway without identifying vehicles or measuring their speed? These are the questions that inspire this research project. Humans are endowed with the ability to grasp the ‘gist’ or overall meaning of a complex visual scene from a single glance and without attention to details. The aim of this project is to develop new computational vision models that combine biological visual processing with probabilistic inference for gist recognition. The developed models will be able to mimic human vision by analysing a complex dynamic scene rapidly and classifying its semantic categories, without identifying individual objects.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220101379
Funder
Australian Research Council
Funding Amount
$417,000.00
Summary
Towards Transferable Visual Understanding in the Real World. This project aims to investigate how to improve the transferability of visual understanding algorithm and system in the real-world applications. This project expects to innovate and advance knowledge in the fields of visual transfer learning and generalizable visual representation learning. Expected outcomes of this project include techniques and algorithms to make the visual understanding system robust to diverse real-world scenarios. ....Towards Transferable Visual Understanding in the Real World. This project aims to investigate how to improve the transferability of visual understanding algorithm and system in the real-world applications. This project expects to innovate and advance knowledge in the fields of visual transfer learning and generalizable visual representation learning. Expected outcomes of this project include techniques and algorithms to make the visual understanding system robust to diverse real-world scenarios. This project should provide significant benefits, such as improving the robustness and safety of autonomous vehicles in transportation area, and reducing the cost of destructive data collection for intelligent fault detection in advanced manufacturing area.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE130101311
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Predicting health status of geriatric patients from user trusted multimedia observations. The information technology developed in this project will provide health care specialists with a better window into the lives of elderly patients. Their behaviour can then be accurately interpreted, potentially leading to earlier recognition of problems and better treatment.
Discovery Early Career Researcher Award - Grant ID: DE190101473
Funder
Australian Research Council
Funding Amount
$387,000.00
Summary
Feature-dependent label noise learning for big data analytics. This project aims to equip machines with the ability to robustly harness feature-dependent label noise from big data. The project expects to produce the potential to explore and exploit the weakly supervised information to better understand, interpret, and infer big data. Expected outcomes of this project include theoretical foundations for learning with label noise in the real-world scenarios and the next generation of intelligent s ....Feature-dependent label noise learning for big data analytics. This project aims to equip machines with the ability to robustly harness feature-dependent label noise from big data. The project expects to produce the potential to explore and exploit the weakly supervised information to better understand, interpret, and infer big data. Expected outcomes of this project include theoretical foundations for learning with label noise in the real-world scenarios and the next generation of intelligent systems to accommodate noisily annotated big data. This project should benefit science, society, and the economy nationally and internationally through the applications in the areas of artificial intelligence, cybersecurity, and big data analytics.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE170101415
Funder
Australian Research Council
Funding Amount
$365,000.00
Summary
Life-long learning in the understanding of big data. This project aims to design and develop computational systems and algorithms that learn as humans do (life-long learning). This will enable systems to automatically interpret Big Data from social media, social network and public surveillance. This project will apply the knowledge learned in auxiliary Big Data sources to effectively interpret target tasks and analyse the communication network (one variant of social network). This project is exp ....Life-long learning in the understanding of big data. This project aims to design and develop computational systems and algorithms that learn as humans do (life-long learning). This will enable systems to automatically interpret Big Data from social media, social network and public surveillance. This project will apply the knowledge learned in auxiliary Big Data sources to effectively interpret target tasks and analyse the communication network (one variant of social network). This project is expected to benefit science, society and the economy, and help governments to better serve the public by improving transport logistics, modelling and regulation, and preventing crime and terrorism.Read moreRead less