Holobody: Advancing the Future of Mixed Reality Technologies. This project aims to advance our understanding and use of mixed reality technologies by pioneering a new approach to interaction in virtual systems that recognises, capitalises on, and expands the potential of the human body as a human-machine interface. The project expects to apply the unique, embodied methodologies of dance and movement technology, integrated with customised software, advanced visualisation and artificial intelligen ....Holobody: Advancing the Future of Mixed Reality Technologies. This project aims to advance our understanding and use of mixed reality technologies by pioneering a new approach to interaction in virtual systems that recognises, capitalises on, and expands the potential of the human body as a human-machine interface. The project expects to apply the unique, embodied methodologies of dance and movement technology, integrated with customised software, advanced visualisation and artificial intelligence, to develop next-generation principles of embodied interaction in virtual systems. Expected outcomes are improved assistive technology, new prototyping techniques for manufacturing, and improved productivity through interactive and immersive systems, benefiting Australian businesses, healthcare and the arts.Read moreRead less
Archiving Australian Media Arts: Towards a method and national collection. The early years of Australian digital media arts heritage are at risk. Australians were significant contributors to the development of media arts internationally, as well as making and exhibiting work nationally, yet only a tiny portion of the digital artwork by Australian artists has made it into institutional collections. Deteriorating disks and reliance on obsolete hardware and software mean that innovative digital pre ....Archiving Australian Media Arts: Towards a method and national collection. The early years of Australian digital media arts heritage are at risk. Australians were significant contributors to the development of media arts internationally, as well as making and exhibiting work nationally, yet only a tiny portion of the digital artwork by Australian artists has made it into institutional collections. Deteriorating disks and reliance on obsolete hardware and software mean that innovative digital preservation and access solutions are needed if these artworks are to be saved. Working with key cultural institutions, this project will conserve key media art case studies from the archives of media arts organisations, and develop a best practice method for the preservation of our digital media arts heritage.Read moreRead less
Play it again: creating a playable history of Australasian digital games, for industry, community and research purposes. This project provides a unique account of the role played by computer games in familiarising the public to new technologies. The computer game industry grosses billions of dollars each year, and yet game technology is quickly superseded. This project redresses this gap by writing histories of the early digital age, and preserving key artefacts.
Play it again: preserving Australian videogame history. This project aims to demonstrate and evaluate the emulation of obsolete operating systems and programs in a cloud-based environment to document, preserve, and exhibit digital cultural heritage. The challenge of preserving and accessing complex digital cultural heritage such as software is one that collecting institutions worldwide are facing. This project will address this challenge by recovering the history of Australian made videogames of ....Play it again: preserving Australian videogame history. This project aims to demonstrate and evaluate the emulation of obsolete operating systems and programs in a cloud-based environment to document, preserve, and exhibit digital cultural heritage. The challenge of preserving and accessing complex digital cultural heritage such as software is one that collecting institutions worldwide are facing. This project will address this challenge by recovering the history of Australian made videogames of the 1990s, preserving significant local digital game artefacts currently at risk, and investigating how these can be exhibited as playable software using the newest emulation techniques. The project expects to generate new knowledge needed by government, museums and industry to inform future strategy and infrastructure investment aimed at making a range of digital cultural heritage available to the public.Read moreRead less
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. Read moreRead less
Visual tracking with environmental constraints. By incorporating high level scene understanding into visual tracking, this project will improve the capacity to monitor and analyse complex patterns of activity in video. This has many applications in public safety and security, but the project will demonstrate it on the challenging task of tracking players during an Australian Football League (AFL) game to gather statistics on their performance.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100090
Funder
Australian Research Council
Funding Amount
$250,000.00
Summary
Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object ....Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics. Read moreRead less
Visual tracking of multiple objects: A stochastic geometrical approach. Reliable real-time visual multiple-object tracking techniques will open up new applications that enhance the quality of life such as driving safety, traffic monitoring, home security, security and surveillance of public facilities. These new applications have huge commercial potentials, and the technology developed from this project will provide the catalyst for vibrant new industries to grow. In addition, the expertise deve ....Visual tracking of multiple objects: A stochastic geometrical approach. Reliable real-time visual multiple-object tracking techniques will open up new applications that enhance the quality of life such as driving safety, traffic monitoring, home security, security and surveillance of public facilities. These new applications have huge commercial potentials, and the technology developed from this project will provide the catalyst for vibrant new industries to grow. In addition, the expertise developed from the project will provide a competitive edge for Australian industries in aerospace, oceanography, robotics, remote sensing, and biomedical engineering. Read moreRead less
ARC Centre of Excellence for Robotic Vision. Robots are vital to Australia's future prosperity in the face of high relative wages, low or decreasing productivity, and impending labour shortages. However the work and workplaces of our most important industries are unstructured and changeable and current robots are challenged by their inability to quickly, safely and reliably "see" and "understand" what is around them. The Centre's research will create the fundamental science and technologies th ....ARC Centre of Excellence for Robotic Vision. Robots are vital to Australia's future prosperity in the face of high relative wages, low or decreasing productivity, and impending labour shortages. However the work and workplaces of our most important industries are unstructured and changeable and current robots are challenged by their inability to quickly, safely and reliably "see" and "understand" what is around them. The Centre's research will create the fundamental science and technologies that will allow robots to see as we do, and overcome the last barrier to the ubiquitous deployment of robots into society for the benefit of all.Read moreRead less