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
Smart Information Processing for Roadside Fire Risk Assessment Using Computational Intelligence and Pattern Recognition. This project proposes a novel approach for identifying roadside fire risks using pattern recognition and computational intelligence techniques. The video data is collected over every state road in Queensland annually, and has the potential to provide a range of value-added products for safer roads. This project aims to develop new techniques for identification of roadside obje ....Smart Information Processing for Roadside Fire Risk Assessment Using Computational Intelligence and Pattern Recognition. This project proposes a novel approach for identifying roadside fire risks using pattern recognition and computational intelligence techniques. The video data is collected over every state road in Queensland annually, and has the potential to provide a range of value-added products for safer roads. This project aims to develop new techniques for identification of roadside objects so that the data can be automatically analysed allowing the estimation of fire risk factors. The final outcome intends to be techniques for segmentation and classification of roadside objects and estimation of fire risk factors.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120100995
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Visual navigation for sunny summer days and stormy winter nights. This project will develop innovative techniques for camera-based navigation that recognise locations under a wide range of environmental conditions caused by day-night cycles, weather and seasonal change. These techniques will enable the widespread use of cheap and lightweight cameras in robot and personal navigation systems.
Taming media for the masses: Computational frameworks for intelligent digital media capture, management, and sharing. The core issues tackled in this project are learning, recognition and application of semantics in multimedia data and the context of its creation and use - a foundational issue in pattern recognition with many applications. The project is part of the Institute for Multi-sensor Processing and Content Analysis whose aim is to tackle technical issues in large scale pattern recogniti ....Taming media for the masses: Computational frameworks for intelligent digital media capture, management, and sharing. The core issues tackled in this project are learning, recognition and application of semantics in multimedia data and the context of its creation and use - a foundational issue in pattern recognition with many applications. The project is part of the Institute for Multi-sensor Processing and Content Analysis whose aim is to tackle technical issues in large scale pattern recognition. By developing scalable and robust techniques to extract information from large scale multi-modal data, the applications include large scale surveillance systems from multi-modal data (e.g. airport security, smart homes for the aged), context-aware devices, and the next generation of media creation and repurposing tools - a fast-growing sector of the economy.Read moreRead less
In search of relevant things: A novel approach for image analysis. This project aims to investigate how experts’ cognitive processes may be transferred to computers for the automatic recognition of visual features. By merging computer and brain sciences, the project will characterise the way the brains of experts understand what is seen, in order to translate such a process in a new computer vision tool. This should provide significant benefits, such as automatic detection of threats or diseases ....In search of relevant things: A novel approach for image analysis. This project aims to investigate how experts’ cognitive processes may be transferred to computers for the automatic recognition of visual features. By merging computer and brain sciences, the project will characterise the way the brains of experts understand what is seen, in order to translate such a process in a new computer vision tool. This should provide significant benefits, such as automatic detection of threats or diseases in satellite and diagnostic imaging, respectively, among other applications. For the first time, the combination of how a computer analyses an image and how an expert interprets it will be used as a common language to enable machines to process visual information in a manner that mimics the way human brains do.Read moreRead less
Superhuman place recognition with a unified model of human visual processing and rodent spatial memory. Current robotic and personal navigation systems leave much to be desired; GPS only works in open outdoor areas, lasers are expensive and cameras are highly sensitive to changing environmental conditions. In contrast, nature has evolved superb navigation systems. This project aims to solve the challenging problem of place recognition, a key component of navigation, by modelling the visual recog ....Superhuman place recognition with a unified model of human visual processing and rodent spatial memory. Current robotic and personal navigation systems leave much to be desired; GPS only works in open outdoor areas, lasers are expensive and cameras are highly sensitive to changing environmental conditions. In contrast, nature has evolved superb navigation systems. This project aims to solve the challenging problem of place recognition, a key component of navigation, by modelling the visual recognition skills of humans and the rodent spatial memory system. This project looks to combine the best understood and most capable components of place recognition in nature to create a whole more capable than its parts, produce advances in robotic and personal navigation technology and lead to breakthroughs in understandings of the brain.Read moreRead less
Image Based Visual Servo Control of Dynamic Under-Actuated Systems. The project builds on earlier work on visual servo control of under-actuated rigid body dynamics to develop and implement sophisticated and robust image based visual servo control for a wide class of under-actuated and fully actuated dynamic systems. The scope of the project extends far beyond basic testing of preliminary results to address key technical issues facing visual servo control algorithms at this time. The project i ....Image Based Visual Servo Control of Dynamic Under-Actuated Systems. The project builds on earlier work on visual servo control of under-actuated rigid body dynamics to develop and implement sophisticated and robust image based visual servo control for a wide class of under-actuated and fully actuated dynamic systems. The scope of the project extends far beyond basic testing of preliminary results to address key technical issues facing visual servo control algorithms at this time. The project is strongly motivated by the host of emerging applications for visual servo control of unmanned aerial vehicles. The experimental program within the project is based on control of a four rotor VTOL `hoverbot'.Read moreRead less
Solve it or Ignore it? The Challenge of Alignment Distortion and Creating Next Generation Automatic Facial Expression Detection. The last two decades have seen an escalating interest in automating the coding of facial expressions. Despite this keen interest, the promise of computer vision systems to accurately code facial expressions in natural circumstances remains elusive. Our interdisciplinary team will research a new paradigm to account for facial alignment distortion directly rather than ai ....Solve it or Ignore it? The Challenge of Alignment Distortion and Creating Next Generation Automatic Facial Expression Detection. The last two decades have seen an escalating interest in automating the coding of facial expressions. Despite this keen interest, the promise of computer vision systems to accurately code facial expressions in natural circumstances remains elusive. Our interdisciplinary team will research a new paradigm to account for facial alignment distortion directly rather than aiming to achieve invariance to it. The project will also research new data agnostic feature compaction capabilities to enable scalable learning on the world’s largest and challenging expression dataset available to us through international collaboration. Tackling these two major open problems will make accurate coding of facial expressions in natural environments achievable.Read moreRead less
Autocalibration without decimation. The insertion of computer generated characters into real footage, the removal of objects from video, and the recovery of 3-dimensional architectural or topographic models from photographs are amongst a growing number of processes used in industry which require highly accurate camera calibration. Autocalibration is thus a prerequisite for these and many other emerging image-based technologies. By developing expertise in this area, and particularly by enabling ....Autocalibration without decimation. The insertion of computer generated characters into real footage, the removal of objects from video, and the recovery of 3-dimensional architectural or topographic models from photographs are amongst a growing number of processes used in industry which require highly accurate camera calibration. Autocalibration is thus a prerequisite for these and many other emerging image-based technologies. By developing expertise in this area, and particularly by enabling more flexible and efficient means of autocalibration, we expect to provide Australian industry with a valuable improvement in the state of the art and a competitive edge in a number of important application areas.Read moreRead less
Learning Robotic Navigation and Interaction from Object-based Semantic Maps. Our project aims to develop new learning algorithms that enable robots to perform high-complexity tasks that are currently impossible. Compared to existing methods that rely on low-level sensor data, we aim to achieve this by learning from a high-level graph representation of the environment that captures semantics, affordances, and geometry. The outcome would be robots capable of using human instructions to efficiently ....Learning Robotic Navigation and Interaction from Object-based Semantic Maps. Our project aims to develop new learning algorithms that enable robots to perform high-complexity tasks that are currently impossible. Compared to existing methods that rely on low-level sensor data, we aim to achieve this by learning from a high-level graph representation of the environment that captures semantics, affordances, and geometry. The outcome would be robots capable of using human instructions to efficiently learn complex interaction and navigation behaviours that transfer to unseen environments. Our research should benefit new applications in domains of economic and societal importance that are currently too complex, unsafe, and uncertain for robot assistants, such as aged care, advanced manufacturing and domestic robotics.Read moreRead less