Two-way Auslan: Automatic Machine Translation of Australian Sign Language. This project aims to develop an automatic two-way machine-translation system between Auslan (Australian Sign Language) and English by researching and leveraging advanced computer vision and machine learning technology. The project expects to advance research in AI technology on topics including visual recognition, language processing and deep learning. This will boost Australia's national research capacity and global com ....Two-way Auslan: Automatic Machine Translation of Australian Sign Language. This project aims to develop an automatic two-way machine-translation system between Auslan (Australian Sign Language) and English by researching and leveraging advanced computer vision and machine learning technology. The project expects to advance research in AI technology on topics including visual recognition, language processing and deep learning. This will boost Australia's national research capacity and global competitiveness. Expected outcomes of this project will help to break the communication barriers between the Deaf and hearing population. This should provide significant benefits to Deaf communities through enhanced communication and improved quality-of-life, leading to a fair, more inclusive and resilient Australian society.Read moreRead less
A Novel Automatic Neural Network Feature Extractor. This project aims to study feature extraction abilities of convolutional as well as traditional neural networks and develop a generic feature extractor which can be applied to wide variety of real-world image and non-image data. New concepts for automatic feature extraction, feature explanation, hybrid evolutionary algorithms and non-iterative ensemble learning will be introduced and evaluated. The expected outcomes are a generic feature extrac ....A Novel Automatic Neural Network Feature Extractor. This project aims to study feature extraction abilities of convolutional as well as traditional neural networks and develop a generic feature extractor which can be applied to wide variety of real-world image and non-image data. New concepts for automatic feature extraction, feature explanation, hybrid evolutionary algorithms and non-iterative ensemble learning will be introduced and evaluated. The expected outcomes are a generic feature extractor for automatically extracting features, an optimiser for finding optimal parameters and non-iterative ensemble learning technique for classification of features into classes. The impact of this project will be automatic feature extractors and classifiers for real-world applications.Read moreRead less
Foundations of Vision Based Control of Robotic Vehicles. Automated and partially automated robotic vehicles are an emerging technology in society. The safety and performance of such systems depends crucially on their sensing and control algorithms. Vision sensing is one of the few sensor modalities that has the potential to adequately represent the complexity of a real world environment. By providing simple and effective vision based control algorithms this project develops Frontier Technologi ....Foundations of Vision Based Control of Robotic Vehicles. Automated and partially automated robotic vehicles are an emerging technology in society. The safety and performance of such systems depends crucially on their sensing and control algorithms. Vision sensing is one of the few sensor modalities that has the potential to adequately represent the complexity of a real world environment. By providing simple and effective vision based control algorithms this project develops Frontier Technologies for Building and Transforming Australian Industries by enabling a wide range of robotic vehicle applications, including aerial, submersible, and wheeled vehicles.Read moreRead less
Automatic Training Data Search and Model Evaluation by Measuring Domain Gap. We aim to investigate computer vision training data and test data, using automatically generated data sets for facial expression recognition and object re-identification. This project expects to quantify and understand the domain gap, the distribution difference between training and test data sets. Expected outcomes of this project are insights on measuring the domain gap, the ability to estimate model performance witho ....Automatic Training Data Search and Model Evaluation by Measuring Domain Gap. We aim to investigate computer vision training data and test data, using automatically generated data sets for facial expression recognition and object re-identification. This project expects to quantify and understand the domain gap, the distribution difference between training and test data sets. Expected outcomes of this project are insights on measuring the domain gap, the ability to estimate model performance without accessing expensive test labels and improvements to system generalisation. This should provide significant benefits for computer vision applications that currently require expensive labelling, and commercial and economic benefits across sectors such as transportation, security and manufacturing.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
Towards in-vehicle situation awareness using visual and audio sensors. This project aims to characterise driver awareness, activity and interactions with other vehicle occupants using visual and audio cues from internally mounted sensors. Road accidents cost Australia an estimated $30 billion per year and tragic loss of thousands of lives, yet the vast majority of severe vehicle crashes are linked to driver fatigue or distraction. The expected project outcomes include advanced artificial intelli ....Towards in-vehicle situation awareness using visual and audio sensors. This project aims to characterise driver awareness, activity and interactions with other vehicle occupants using visual and audio cues from internally mounted sensors. Road accidents cost Australia an estimated $30 billion per year and tragic loss of thousands of lives, yet the vast majority of severe vehicle crashes are linked to driver fatigue or distraction. The expected project outcomes include advanced artificial intelligence to infer and predict dangerous driver and passenger behaviour. This has the potential to significantly benefit society by advancing autonomous driving capabilities and reducing driver-induced accidents and fatalities, ensuring that every driver, passenger and pedestrian arrives home safely at the end of each day.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE150101365
Funder
Australian Research Council
Funding Amount
$360,000.00
Summary
In-person tele-presence through hybrid camera networks. This project aims to develop novel theories and algorithms for live capturing of accurate dense 3D models of moving subjects based on hybrid camera networks. The latter consist of a mix of static external red, green, blue plus depth (RGB-D) cameras and a dynamic head-mounted regular camera. The scientific novelties will be dense, non-rigid, and collaborative structure-from-motion theories that maximise the exploitation of such hybrid inform ....In-person tele-presence through hybrid camera networks. This project aims to develop novel theories and algorithms for live capturing of accurate dense 3D models of moving subjects based on hybrid camera networks. The latter consist of a mix of static external red, green, blue plus depth (RGB-D) cameras and a dynamic head-mounted regular camera. The scientific novelties will be dense, non-rigid, and collaborative structure-from-motion theories that maximise the exploitation of such hybrid information, for instance by utilising exact head-pose information. The outcome is a working prototype producing live full-body animations, thus leveraging new applications in the Information Technology industry. Highly strategically relevant examples are given by 3D tele-presence, enhanced tele-operation, robotics, and intelligent transportation systems.Read moreRead less
Exploiting the Symmetry of Spatial Awareness for 21st Century Automation. This project aims to enable autonomous robotic systems to operate more robustly and more reliably in the complex, cluttered and dynamic environments found in real-world applications. Applying the latest understanding of symmetry in non-linear systems and control provides tools that can be used to develop new design methodologies for spatial awareness algorithms. The outcomes of this project should increase Australia's ca ....Exploiting the Symmetry of Spatial Awareness for 21st Century Automation. This project aims to enable autonomous robotic systems to operate more robustly and more reliably in the complex, cluttered and dynamic environments found in real-world applications. Applying the latest understanding of symmetry in non-linear systems and control provides tools that can be used to develop new design methodologies for spatial awareness algorithms. The outcomes of this project should increase Australia's capacity in high-tech systems and deliver world best open source code for spatial awareness problems to enable the next generation of automation in Australia.Read moreRead less