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
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.Read moreRead less
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.Read moreRead less
Assistive micro-navigation for vision impaired people. This project aims to develop novel algorithms to transform a simple camera into a smart sensor, that can enable a vision-impaired person to navigate freely and without additional aids in a crowded area. Such a smart sensor will be endowed with the capability to detect and locate obstacles, identify the walking path, recognise objects and traffic signs and convey step-by-step instructions to the user. The project outcomes are expected to impr ....Assistive micro-navigation for vision impaired people. This project aims to develop novel algorithms to transform a simple camera into a smart sensor, that can enable a vision-impaired person to navigate freely and without additional aids in a crowded area. Such a smart sensor will be endowed with the capability to detect and locate obstacles, identify the walking path, recognise objects and traffic signs and convey step-by-step instructions to the user. The project outcomes are expected to improve the well-being and accessibility to public areas for vision-impaired people and reduce physical access disparities for this disadvantaged and vulnerable group. Furthermore, technologies developed in this project can potentially be adapted for use in related special navigation applications such as road safety, self-driving vehicles, and autonomous robots.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: 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
Making Meta-learning Generalised . This project aims to develop novel machine learning techniques, termed generalised meta-learning, to make machines better utilise past experience to solve new tasks with few data. It expects to reduce the undesirable dependence of current machine learning on labelled data and significantly expand its application scope. Expected outcomes of the project consist of new theoretical results on meta-learning and a set of innovative algorithms that can support the bui ....Making Meta-learning Generalised . This project aims to develop novel machine learning techniques, termed generalised meta-learning, to make machines better utilise past experience to solve new tasks with few data. It expects to reduce the undesirable dependence of current machine learning on labelled data and significantly expand its application scope. Expected outcomes of the project consist of new theoretical results on meta-learning and a set of innovative algorithms that can support the building of next generation of computer vision systems to work in open and dynamic environments. This should be able to produce solid benefits to the science, society, and economy of Australian via the application of these advanced intelligent systems.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: DE190101315
Funder
Australian Research Council
Funding Amount
$401,886.00
Summary
Towards extreme object detection. This project aims to provide a comprehensive and practical extreme object detection system considering three extreme object detection challenges, that is small and distance objects, occluded objects and sparse (rare) objects. Reliable extreme object detection is critical for intelligent agents in many aspects and is becoming increasingly important for developing a smart nation by building intelligent transportation and smart cities. To design and develop such an ....Towards extreme object detection. This project aims to provide a comprehensive and practical extreme object detection system considering three extreme object detection challenges, that is small and distance objects, occluded objects and sparse (rare) objects. Reliable extreme object detection is critical for intelligent agents in many aspects and is becoming increasingly important for developing a smart nation by building intelligent transportation and smart cities. To design and develop such an effective system, this project provides novel scale-invariant learning, occlusion-robust learning and semi-supervised learning solutions to address the corresponding challenges. The project is expected to have a significant impact on a broad array of application areas including autonomous vehicles, robotics, and intelligent surveillance cameras.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