Autonomous Functions for Smart Cars. The aim of this project is to develop autonomous functions for smart cars, such as lane departure warning, driver fatigue warning, and automatic lane following. Every year 70,000 people are killed in road accidents, 95% of which can be attributed to driver error. The potential outcomes of this project therefore significant. Many of the theoretical methods required for this project have been developed by our group. However, further theoretical refinements fo ....Autonomous Functions for Smart Cars. The aim of this project is to develop autonomous functions for smart cars, such as lane departure warning, driver fatigue warning, and automatic lane following. Every year 70,000 people are killed in road accidents, 95% of which can be attributed to driver error. The potential outcomes of this project therefore significant. Many of the theoretical methods required for this project have been developed by our group. However, further theoretical refinements followed by experimental verification is necessary. For smart cars to be accepted, the systems must be demonstrated to be reliable and to operate in a wide range of conditions.Read moreRead less
Learning clique potentials for high-order graphical models. This project aims to develop algorithms for computers to automatically learn about visual scenes and objects from images. Using our algorithms, computers will be able to find objects and describe scenes in single images or large image collections such as online photo albums.
Lifelong robotic navigation using visual perception. Service robots are becoming a major part of our working and personal environments, in much the same way as personal computers already have. This project will develop new methods of practical and useful robot navigation that will enable Australia's industries and services to remain internationally competitive.
User-task co-adaptation for effective interactive simulation environments. This project aims to deliver smart interactive simulation environments in which users and simulation tasks work together. This project aims to create novel adaptive algorithms to automatically discover those user and task features that vary together to smartly adapt users and simulation tasks to work together harmoniously, seamlessly and effectively. Interactive simulation environments are the backbone for evaluating conc ....User-task co-adaptation for effective interactive simulation environments. This project aims to deliver smart interactive simulation environments in which users and simulation tasks work together. This project aims to create novel adaptive algorithms to automatically discover those user and task features that vary together to smartly adapt users and simulation tasks to work together harmoniously, seamlessly and effectively. Interactive simulation environments are the backbone for evaluating concepts, designs, products and advanced training systems in industry and government organisations. By bringing the user naturally inside the simulation as a task's component, users can improve their experience while task performance is simultaneously optimised. Intended outcomes include novel dynamic user-task profiling algorithms and new adaptive algorithms for user-task co-adaptation. Practical outcomes may include robust and highly effective simulation environments.Read moreRead less
Enhanced ultrasound-based imaging using image-based registration and acoustic impedance reconstruction. The project will nurture the development of a new centre for medical image analysis work in Australia at the ANU. This is in line with the vision of ANU's Department of Engineering for the growth of biomedical engineering research. The project is directed at the creation of new surgical and imaging techniques based on ultrasound. These will have a direct effect on improved healthcare and new c ....Enhanced ultrasound-based imaging using image-based registration and acoustic impedance reconstruction. The project will nurture the development of a new centre for medical image analysis work in Australia at the ANU. This is in line with the vision of ANU's Department of Engineering for the growth of biomedical engineering research. The project is directed at the creation of new surgical and imaging techniques based on ultrasound. These will have a direct effect on improved healthcare and new clinical procedures. The creation of a new ultrasound imaging modality will have commercial applications, enhancing the growth of biomedical engineering in Australia. The training of new PhD students and postdoctoral fellows will provide a basis for further development in this area, and its extension to other imaging research in Australia. Read moreRead less
Pattern Recognition and Scene Analysis via Machine Learning. We plan to use kernel methods, a novel machine learning technique, for computer vision problems, such as scene analysis and real time object recognition. Such capabilities are relevant for the design of intelligent and adaptive systems, suitable for complex real world environments. Expected outcomes are the design of efficient statistical tools which take the special nature of visual data into account (structure, decomposition, prior ....Pattern Recognition and Scene Analysis via Machine Learning. We plan to use kernel methods, a novel machine learning technique, for computer vision problems, such as scene analysis and real time object recognition. Such capabilities are relevant for the design of intelligent and adaptive systems, suitable for complex real world environments. Expected outcomes are the design of efficient statistical tools which take the special nature of visual data into account (structure, decomposition, prior knowledge of physical environments, etc.) and combine the advantages of feature based high-level vision methods with low-level machine learning techniques.
This proposal is part of a joint IST project with partners from the European Union.Read moreRead less
Leveraging 3D computer vision for camera-based precise geo-localisation. This project aims to develop advanced 3D computer vision and image processing technology that can turn regular cameras into high-precision location-sensing devices. Spatial Location is a fundamental type of information of our physical world. Determining the precise location of people, vehicle, and mobile devices is essential for many critical applications. Outcomes of the project will enable a wide range of novel applicatio ....Leveraging 3D computer vision for camera-based precise geo-localisation. This project aims to develop advanced 3D computer vision and image processing technology that can turn regular cameras into high-precision location-sensing devices. Spatial Location is a fundamental type of information of our physical world. Determining the precise location of people, vehicle, and mobile devices is essential for many critical applications. Outcomes of the project will enable a wide range of novel applications of significant social, environmental and economic value, such as Location-Aware Service, Environment Monitoring, Augmented Reality, Autonomous Vehicle, and Rapid Emergency Response. The project will enhance Australia's international competitive advantage in forefront of ICT research and technology innovation.Read moreRead less
Semantic Vectorisation: From Bitmaps to Intelligent Representations. The objective of this innovative project is to provide a solution to the open question of representing natural images by semantically rich vector graphics. The challenges are to identify key visual and temporal elements for images and videos, and efficiently decompose the visual data into semantic vector representations that are faithful to original data, compact and editable. The project aims to investigate new bitmap-to-vecto ....Semantic Vectorisation: From Bitmaps to Intelligent Representations. The objective of this innovative project is to provide a solution to the open question of representing natural images by semantically rich vector graphics. The challenges are to identify key visual and temporal elements for images and videos, and efficiently decompose the visual data into semantic vector representations that are faithful to original data, compact and editable. The project aims to investigate new bitmap-to-vector conversion methods. It is expected to develop a framework where semantic labels and hyperlinks can be embedded in visual data automatically. It hopes to pioneer the creation of a web of images where the links are on image/video regions. New image simplification, stylisation, and non-photorealistic rendering methods are expected to be provided.Read moreRead less
Computer Vision Optimization Problems Using Machine Learning. Computer Vision concerns itself with understanding the world through the analysis of images obtained by a video or still camera. An important application is tracking of people in video and modelling their movements. This has evident applications in security, sport and entertainment. By enabling the computer to capture the motion of a subject in a video, we may detect suspicious activity in security, analyze the motion (golf-swing, ....Computer Vision Optimization Problems Using Machine Learning. Computer Vision concerns itself with understanding the world through the analysis of images obtained by a video or still camera. An important application is tracking of people in video and modelling their movements. This has evident applications in security, sport and entertainment. By enabling the computer to capture the motion of a subject in a video, we may detect suspicious activity in security, analyze the motion (golf-swing, diving style) of a sports-person, or capture the motion of an actor for animation or game applications. Development of a reliable technology requires new optimization techniques, which will place Australia at the forefront of the application of such research, commercially and for the public benefit.Read moreRead less
Added depth: automated high level image interpretation. Humans are very good at understanding the world through imagery, but computers lack this fundamental capacity because they lack experience of what they might see. This project will provide this experience by combining the large volumes of imagery on the Internet with three dimensional information generated by humans for other purposes.