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
Interactive and scalable media over software defined networks. A novel API and associated algorithms will be developed to exploit the emerging technology of software defined networks (SDN) for improving the efficiency and responsiveness of interactive media browsing applications. The approach applies to conventional streaming video as well as more interactive services based on scalable media compression and communication technology, notably JPIP (IS15444-9) video. Recent advances in motion codin ....Interactive and scalable media over software defined networks. A novel API and associated algorithms will be developed to exploit the emerging technology of software defined networks (SDN) for improving the efficiency and responsiveness of interactive media browsing applications. The approach applies to conventional streaming video as well as more interactive services based on scalable media compression and communication technology, notably JPIP (IS15444-9) video. Recent advances in motion coding will be combined with new spatio-temporal transforms to develop an efficient inter-frame extension to the JPEG 2000 standard that is fully compatible with JPIP. Each of these innovations is important in its own right, but together they will facilitate a highly compelling interactive media browsing experience.Read moreRead less
Enhancing sensory perception and balance control in HMD-based VR. This project seeks to test a revolutionary new theoretical framework for understanding how we perceive our self-motion and maintain postural control when immersed in head-mounted display (HMD) virtual reality (VR). Photorealistic graphical simulations and artificial vestibular stimulation will be used to investigate how visual and non-visual information concerning self-motion is integrated in the brain. The outcomes will reveal ho ....Enhancing sensory perception and balance control in HMD-based VR. This project seeks to test a revolutionary new theoretical framework for understanding how we perceive our self-motion and maintain postural control when immersed in head-mounted display (HMD) virtual reality (VR). Photorealistic graphical simulations and artificial vestibular stimulation will be used to investigate how visual and non-visual information concerning self-motion is integrated in the brain. The outcomes will reveal how multisensory interaction influences our sensory perception and postural control during HMD VR. The knowledge gained is expected to generate new economic benefits by inspiring next-generation technologies that will optimise users' immersive experiences (e.g., virtual exploration and immersive gaming).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.
Nonlinear Transfer Distance Metric Learning for Gleaning Knowledge from the Crowd. This project will develop nonlinear transfer distance metric learning algorithms for training and test samples that are not independent and identically distributed, or from different instance spaces. New theoretical foundations for crowd-sourcing will lead to innovative intelligent systems for such purposes as the NBN, social, and security services, and keep pace with developments in hardware technology. The outco ....Nonlinear Transfer Distance Metric Learning for Gleaning Knowledge from the Crowd. This project will develop nonlinear transfer distance metric learning algorithms for training and test samples that are not independent and identically distributed, or from different instance spaces. New theoretical foundations for crowd-sourcing will lead to innovative intelligent systems for such purposes as the NBN, social, and security services, and keep pace with developments in hardware technology. The outcomes include applications in social networks, the Internet, and climate change, as well as video surveillance to help combat crime and terrorism. The innovative research will significantly benefit Australia’s economy, environment and society, and will maintain Australia's global leading role in the machine learning and computer vision.Read moreRead less
Streaming label learning for leaching knowledge from labels on the fly. This machine intelligence project aims to explore the potential to use and incorporate past knowledge and training to better understand, interpret and develop new concepts. The expected outcomes will provide major technological breakthroughs to benefit science, society, and the economy nationally by laying theoretical foundations for learning labels in a streaming fashion, and building the next generation of intelligent syst ....Streaming label learning for leaching knowledge from labels on the fly. This machine intelligence project aims to explore the potential to use and incorporate past knowledge and training to better understand, interpret and develop new concepts. The expected outcomes will provide major technological breakthroughs to benefit science, society, and the economy nationally by laying theoretical foundations for learning labels in a streaming fashion, and building the next generation of intelligent systems to accommodate environment change in applications about cybercrime, terrorism, and emergence.Read moreRead less
Challenging the Bystander Effect via documentary film. This project aims to challenge the Bystander Effect. Social experiments from the 1960s have entrenched the view that in groups we fail to act to prevent harm to others in public emergencies. Film has played a significant role in promoting this theory. Drawing on an innovative screen performance method, this project is likely to generate knowledge about how bystanders can co-ordinate their actions to safely intervene; it will result in an inn ....Challenging the Bystander Effect via documentary film. This project aims to challenge the Bystander Effect. Social experiments from the 1960s have entrenched the view that in groups we fail to act to prevent harm to others in public emergencies. Film has played a significant role in promoting this theory. Drawing on an innovative screen performance method, this project is likely to generate knowledge about how bystanders can co-ordinate their actions to safely intervene; it will result in an innovative and accessible documentary. The project has the capacity to contribute to a reduction of violence in public spaces and more effective responses in the face of emergencies.Read moreRead less
Reinterpreting Milgram's obedience studies via documentary film. One of the hardest dilemmas we can face is responding to directions which go against our conscience. Stanley Milgram's 'obedience to authority' paradigm appears to show that most of us will comply. Fifty years after his landmark film 'Obedience', this multidisciplinary project will re-examine his hugely influential but often misunderstood work.
Efficient multi-view video coding with cuboids and base anchored models. This project aims to address current deficiencies in multi-view video coding technology to achieve the ultra-compression efficiency demanded by increasing display resolutions and synchronised viewpoints. The project expects to generate new knowledge, by moving from the current pixel-centric approach to methods that concentrate information common to many view-frames. The project is expected to improve compression of audio-vi ....Efficient multi-view video coding with cuboids and base anchored models. This project aims to address current deficiencies in multi-view video coding technology to achieve the ultra-compression efficiency demanded by increasing display resolutions and synchronised viewpoints. The project expects to generate new knowledge, by moving from the current pixel-centric approach to methods that concentrate information common to many view-frames. The project is expected to improve compression of audio-visual services that are of great interest to international standards bodies and industry, while facilitating free interaction and augmented reality. This project will provide significant benefits to broadcast, entertainment, surveillance and health industries and position Australia as a world leader in this field.Read moreRead less
Automatic Machine Learning with Imperfect Data for Video Analysis . This project aims to propose new algorithms and technologies for constructing an efficient video analysis system, which will be aligned with Australia’s science and research priorities. Specifically, during this project, a novel network structure search method based on auto machine learning will be proposed, an unsupervised domain adaptation algorithm will be developed, and a generative data augmentation method will be construct ....Automatic Machine Learning with Imperfect Data for Video Analysis . This project aims to propose new algorithms and technologies for constructing an efficient video analysis system, which will be aligned with Australia’s science and research priorities. Specifically, during this project, a novel network structure search method based on auto machine learning will be proposed, an unsupervised domain adaptation algorithm will be developed, and a generative data augmentation method will be constructed. All of these will construct a stable and efficient deep neural network, which is able to process large size videos captured from real scenarios in high efficiencies. Various fields, such as health care service and cybersecurity, will benefit hugely from this project.Read moreRead less