Neural mechanisms for visual target detection and attention in complex scenes. This project will study neurons in the insect brain that solve one of the biggest problems for computer vision systems - tracking the motion of tiny targets moving against strongly camouflaged backgrounds. The results will be used to develop a novel biologically inspired model for target tracking with applications for smart cameras and robotics.
Strategies for neural summation in space and time for night vision. This project will study motion vision in nocturnal and day-active insects to understand how the brain sees in darkness, even when individual light sensitive cells in the eye perform poorly. This will help to identify optimal strategies that have evolved in nature to deal with noisy signals in low light and has implications for man-made night cameras.
From insects to robots: how brains make predictions and ignore distractions. This project aims to address fundamental questions in neuroscience and to integrate this biological understanding with the development of leading-edge robotics. Whether a human catching a ball or a dragonfly feeding in a swarm, brains have the remarkable ability to predict the future location of moving targets. The brain predicts in the presence of distractions and even if the target disappears, for example, when hidden ....From insects to robots: how brains make predictions and ignore distractions. This project aims to address fundamental questions in neuroscience and to integrate this biological understanding with the development of leading-edge robotics. Whether a human catching a ball or a dragonfly feeding in a swarm, brains have the remarkable ability to predict the future location of moving targets. The brain predicts in the presence of distractions and even if the target disappears, for example, when hidden behind another object. This project will investigate how brains use both environmental and internal information to select a target and predict its future location. By implementing bio-inspired computations in hardware, this project aims to provide significant benefits such as improving autonomous systems for defence, health and transportation.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE150100548
Funder
Australian Research Council
Funding Amount
$359,000.00
Summary
Neural and robotic correlates of predictive coding and selective attention. Whether a human catching a ball, a dog leaping at a frisbee or a dragonfly hunting prey amidst a swarm, brains both large and small have evolved the ability to focus attention on one moving target, even in the presence of distracters. This project aims to investigate how brains solve this challenging problem by recording the activity of dragonfly neurons that selectively attend to one target whilst ignoring others. The p ....Neural and robotic correlates of predictive coding and selective attention. Whether a human catching a ball, a dog leaping at a frisbee or a dragonfly hunting prey amidst a swarm, brains both large and small have evolved the ability to focus attention on one moving target, even in the presence of distracters. This project aims to investigate how brains solve this challenging problem by recording the activity of dragonfly neurons that selectively attend to one target whilst ignoring others. The project aims to examine how expectation and attention are encoded in the brain and will build an autonomous robot using computational models bio-inspired from this neuronal processing. Robots capable of visually perceiving and interacting with targets in natural environments have applications in health, surveillance and defence.Read moreRead less
Target detection in visual clutter. The interdisciplinary nature of the project will offer a stimulating environment for training a postdoctoral worker in the hot topic of computational neuroscience. While computationally expensive solutions to moving target detection in clutter have been implemented using conventional engineering, this project will offer insight into the efficiency of the biological brain (with benefit of millions of years of evolution towards compact, economical and optimal so ....Target detection in visual clutter. The interdisciplinary nature of the project will offer a stimulating environment for training a postdoctoral worker in the hot topic of computational neuroscience. While computationally expensive solutions to moving target detection in clutter have been implemented using conventional engineering, this project will offer insight into the efficiency of the biological brain (with benefit of millions of years of evolution towards compact, economical and optimal solutions). The results will assist development of efficient artificial intelligence. It will also assist our ongoing collaborations with defence partners to develop and apply algorithms in artificial vision systems. Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0561231
Funder
Australian Research Council
Funding Amount
$671,715.00
Summary
MRI GRID Computing Facility: Design, Optimisation and Image Processing. The MRI Grid Computing Facility provides the IT infrastructure to achieve effective e-research in the area of magnetic resonance (MR) imaging, a field of neuroscience research that revolutionizes the way brain diseases are identified and treated. The facility consists of a dedicated high performance grid compute engine, distributed visualisation workstations, and distributed data warehouse facilities. Software tools acc ....MRI GRID Computing Facility: Design, Optimisation and Image Processing. The MRI Grid Computing Facility provides the IT infrastructure to achieve effective e-research in the area of magnetic resonance (MR) imaging, a field of neuroscience research that revolutionizes the way brain diseases are identified and treated. The facility consists of a dedicated high performance grid compute engine, distributed visualisation workstations, and distributed data warehouse facilities. Software tools accessible through the Internet will enable researchers to archive, retrieve and exchange data and software; access distributed MR image databases and the latest MR image analysis tools; schedule analysis tasks on the grid compute engine, the outcomes of which will be visualized by the visualization workstations.Read moreRead less
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
Tracking targets in large scale surveillance camera networks. The research is expected to provide a significant boost in the effectiveness of safety and security measures for public facilities and open spaces that are monitored by surveillance cameras. The general public benefits from this through a decreased need for intrusive security measures, and increased deterrence of crime and anti-social behaviour. This capability is in demand worldwide for both public and private camera networks, whose ....Tracking targets in large scale surveillance camera networks. The research is expected to provide a significant boost in the effectiveness of safety and security measures for public facilities and open spaces that are monitored by surveillance cameras. The general public benefits from this through a decreased need for intrusive security measures, and increased deterrence of crime and anti-social behaviour. This capability is in demand worldwide for both public and private camera networks, whose usefulness is currently limited by the difficulty of monitoring them. We therefore anticipate considerable commercial interest in Australia and internationally.
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Image search for simulator content creation. The World Wide Web contains tens of billions of images, with personal and industrial collections stretching to may times that number. The potential economic value of these image-based resources is enormous, but largely untapped as we have no practical way of recovering the images we need. This project will develop image search technologies which will allow Australian industry to exploit these important resources. Some of the wide variety of possible ....Image search for simulator content creation. The World Wide Web contains tens of billions of images, with personal and industrial collections stretching to may times that number. The potential economic value of these image-based resources is enormous, but largely untapped as we have no practical way of recovering the images we need. This project will develop image search technologies which will allow Australian industry to exploit these important resources. Some of the wide variety of possible applications might include the searching of surveillance video for objects of interest, vision-based guidance of unmanned vehicles, smart-phone and smart-home systems which understand their environments, and stock tracking systems which can detect spoilage.Read moreRead less
Deep visual understanding: learning to see in an unruly world. Deep Learning has achieved incredible success at an astonishing variety of Computer Vision tasks recently. This project aims to convey this success into the challenging domain of high-level image-based reasoning. It will extend deep learning to achieve flexible semantic reasoning about the content of images based on information gleaned from the huge volumes of data available on the Internet. The project expects to overcome one of the ....Deep visual understanding: learning to see in an unruly world. Deep Learning has achieved incredible success at an astonishing variety of Computer Vision tasks recently. This project aims to convey this success into the challenging domain of high-level image-based reasoning. It will extend deep learning to achieve flexible semantic reasoning about the content of images based on information gleaned from the huge volumes of data available on the Internet. The project expects to overcome one of the primary limitations of deep learning and will greatly increase its practical application to a range of industrial, cultural or health settings.Read moreRead less