Subband centroids and deep neural networks for robust speech recognition. This project aims to improve the robustness and accuracy of automatic speech and speaker recognition systems. Though these systems work reasonably well in noise-free environments, their performance deteriorates drastically even in the presence of a small amount of noise. To overcome this problem, this project proposes a missing-feature approach for robust speech and speaker recognition. This approach is expected to make th ....Subband centroids and deep neural networks for robust speech recognition. This project aims to improve the robustness and accuracy of automatic speech and speaker recognition systems. Though these systems work reasonably well in noise-free environments, their performance deteriorates drastically even in the presence of a small amount of noise. To overcome this problem, this project proposes a missing-feature approach for robust speech and speaker recognition. This approach is expected to make the speech and speaker recognition systems less sensitive to additive background noise and make them more useful in telecommunications and business.Read moreRead less
Enhancing the Australian theme park experience by harnessing virtual-physical play. This project will deliver methodologies for designing games enriched by virtual-physical play. The project will contribute to furthering Australia's lead in the production of compelling theme park experiences, computer games and interactive training systems. The entertainment, digital media and information and communications technology industries will all benefit as a result.
Improved decoding of human brain activity using advanced functional magnetic resonance imaging at ultra-high field strength. Using advanced MRI methods at ultra-high field, this project aims to enable the decoding and reconstruction of visual stimuli, as well as imagined ones from small functional units (layers and columns) in the human brain in vivo. This will be made possible by the use of a new functional MRI method, concurrent high temporal and spatial resolution and whole brain coverage as ....Improved decoding of human brain activity using advanced functional magnetic resonance imaging at ultra-high field strength. Using advanced MRI methods at ultra-high field, this project aims to enable the decoding and reconstruction of visual stimuli, as well as imagined ones from small functional units (layers and columns) in the human brain in vivo. This will be made possible by the use of a new functional MRI method, concurrent high temporal and spatial resolution and whole brain coverage as well as high sensitivity and specificity. Additionally, it will advance the development of functional connectomics and the aid the parcellation of the human cortex.Read moreRead less
Design of adaptive learning visual sensor networks for crowd modelling in high-density and occluded scenarios. Partnering University of Melbourne researchers, with video surveillance experts SenSen, engineering consultants ARUP and the Melbourne Cricket Club, the project addresses research enabling a system-integrating, existing surveillance, infrastructure to model crowd behaviour and exit strategies, providing real-time analysis, prediction and response capabilities for venue managers and emer ....Design of adaptive learning visual sensor networks for crowd modelling in high-density and occluded scenarios. Partnering University of Melbourne researchers, with video surveillance experts SenSen, engineering consultants ARUP and the Melbourne Cricket Club, the project addresses research enabling a system-integrating, existing surveillance, infrastructure to model crowd behaviour and exit strategies, providing real-time analysis, prediction and response capabilities for venue managers and emergency services. This new capability enhances utilisation of security resources to prevent injury and fatalities in evacuation scenarios, applicable to existing venues and influencing the development of new facilities around the country. The project delivers researcher training, global clientele for local technology and a platform for local industry growth.Read moreRead less
Advanced Computer Vision Techniques for Marine Ecology. Ever expanding human activity coupled with climate change has severely damaged marine ecosystems, which play a key role in our planet's ability to sustain life. Yet automated technology to monitor the health of our oceans still does not exist, with marine scientists still having today to process manually a massive amount of raw underwater imagery. This research aims to address this bottleneck by developing advanced computer vision tools for ....Advanced Computer Vision Techniques for Marine Ecology. Ever expanding human activity coupled with climate change has severely damaged marine ecosystems, which play a key role in our planet's ability to sustain life. Yet automated technology to monitor the health of our oceans still does not exist, with marine scientists still having today to process manually a massive amount of raw underwater imagery. This research aims to address this bottleneck by developing advanced computer vision tools for rapid, large-scale, automatic identification of marine species. Such an automated technology is expected to greatly benefit marine ecological studies in terms of speed, cost, accuracy of the spatial/temporal sampling and thus in better quantifying the level of environmental change marine ecosystems can tolerate.Read moreRead less
Improving the face of cosmetic medicine - an automatic three-dimensional facial analysis system for facial rejuvenation. 'How will I look?' is the most common question to cosmetic doctors from patients considering facial rejuvenation. This project will answer this question for the first time by providing patients with a three-dimensional model of their post-treatment face as well as informing cosmetic doctors exactly how to achieve the patient's desired face.
Machine Learning for Fracture Risk Assessment from Simple Radiography. This project aims to develop a novel, reliable, low-cost system to detect poor bone health and assess fracture risk to help to prevent and manage osteoporosis-related fractures. Currently, osteoporosis-related fractures cost our health system millions of dollars annually and costs are increasing with our ageing population. Early detection of poor bone health will improve the effectiveness of preventive measures and ease this ....Machine Learning for Fracture Risk Assessment from Simple Radiography. This project aims to develop a novel, reliable, low-cost system to detect poor bone health and assess fracture risk to help to prevent and manage osteoporosis-related fractures. Currently, osteoporosis-related fractures cost our health system millions of dollars annually and costs are increasing with our ageing population. Early detection of poor bone health will improve the effectiveness of preventive measures and ease this burden. Current methods include unreliable, crude clinical and visual guides that suggest osteoporosis screening. The project plans to develop a novel system by applying machine learning algorithms to radiology data which is commonly captured for diagnosing other conditions.Read moreRead less
Advanced three-dimensional Computer Vision Algorithms for 'Find and Grasp' Future Robots. This project addresses crucial limitations of existing vision systems for the robot grasping of irregular objects in messy living environments. This project aims to undertake fundamental research into novel three-dimensional vision algorithms, exploiting multiple modalities (two-dimensional+three-dimensional+video) for scene labelling, object classification, scene segmentation and grasp synthesis to enable ....Advanced three-dimensional Computer Vision Algorithms for 'Find and Grasp' Future Robots. This project addresses crucial limitations of existing vision systems for the robot grasping of irregular objects in messy living environments. This project aims to undertake fundamental research into novel three-dimensional vision algorithms, exploiting multiple modalities (two-dimensional+three-dimensional+video) for scene labelling, object classification, scene segmentation and grasp synthesis to enable future robots to operate in unstructured environments with highly occluded and cluttered objects. It is expected to significantly advance research and to have broad applications, including home robotics to improve the quality of life of elders and people with special needs. These algorithms may also be used in security (explosive manipulation) and agriculture (field crop harvesting).Read moreRead less
Compression of distributed data: bridging the gap between theory and practice. In bushfire and tsunami early warning systems, environmental monitoring and healthcare applications, distributed sensors collect and transmit correlated data. This project will design novel data compression algorithms that exploit this correlation to dramatically increase the performance of existing networks and enable new applications.
New high-performance iterative error correction codes. This project develops new error correction codes to underpin the success of next-generation communications technologies. The nature of the project presents significant potential for project outcomes to be beneficial to the Australian telecommunications industry in a wide range of application areas from optical communication to digital broadcasting.