Statistical Methods of Model Fitting and Segmentation in Computer Vision. Electronic sensors such as cameras and lasers can provide a rich source of information about the position, shape, and motion of objects around us. However, to extract this information in a reliable, automatic, and accurate way requires a sophisticated statistical theory of the process. Example applications include: video surveillance (better automatic detection of moving people and vehicles and of characterising what those ....Statistical Methods of Model Fitting and Segmentation in Computer Vision. Electronic sensors such as cameras and lasers can provide a rich source of information about the position, shape, and motion of objects around us. However, to extract this information in a reliable, automatic, and accurate way requires a sophisticated statistical theory of the process. Example applications include: video surveillance (better automatic detection of moving people and vehicles and of characterising what those people and vehicles are doing), industrial prototyping and inspection (measuring the size and shape of objects), urban planning (laser scanning streetscapes to create computer models of cities), entertainment industry (movie special effects and games), etc. Read moreRead less
Robust face detection and recognition for computer-based security surveillance. The research aims at improving the existing and creating new automated face detection and recognition methods by making them invariant, firstly to head pose, orientation, scale and rotation, and then to occlusion, lighting conditions and facial expressions.
A robust face detector will be developed first and then a new face recognition algorithm that continues to learn identity-specific discriminants on-line by co ....Robust face detection and recognition for computer-based security surveillance. The research aims at improving the existing and creating new automated face detection and recognition methods by making them invariant, firstly to head pose, orientation, scale and rotation, and then to occlusion, lighting conditions and facial expressions.
A robust face detector will be developed first and then a new face recognition algorithm that continues to learn identity-specific discriminants on-line by collecting incremental face exemplars. The result of the research will be an algorithm that can improve its performance on-line adapting in a stable learning process each identity model to the correct facial examples.
The research has significant practical implication in visual surveillance increasing the robustness of identification of person identity, state and intent.
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Visualisation of large, complex networks through small, beautiful diagrams. Data is increasingly organised as networks. Visualisation is a key way to understand networks. This project plans to develop a new paradigm for this task. Using modern generic constrained optimisation techniques it will produce layouts for small graphs whose quality is similar to that produced by hand, something that is not possible with current approaches. These algorithms will then be used to visualise large graphs. In ....Visualisation of large, complex networks through small, beautiful diagrams. Data is increasingly organised as networks. Visualisation is a key way to understand networks. This project plans to develop a new paradigm for this task. Using modern generic constrained optimisation techniques it will produce layouts for small graphs whose quality is similar to that produced by hand, something that is not possible with current approaches. These algorithms will then be used to visualise large graphs. Instead of simply trying to visualise every node and link in the graph. The project will develop techniques to extract useful subsets or abstractions that are as small possible, yet sufficient to answer targeted queries. The techniques for producing small high-quality diagrams will then be applicable to presenting these focused visualisations.Read moreRead less
Methodologies for automatic visual identification in heat detection aids. New techniques will be designed and developed to automate the existing manual heat detection of cattle, under general imaging conditions. The proposed intelligent system will consist of six stages: 1- image acquisition, 2- image preprocessing, 3- presence detection, 4- illumination compensation, 5- HD detection, and 6- heat detection. The proposed system will handle various image variations, and will be fast and cost-effec ....Methodologies for automatic visual identification in heat detection aids. New techniques will be designed and developed to automate the existing manual heat detection of cattle, under general imaging conditions. The proposed intelligent system will consist of six stages: 1- image acquisition, 2- image preprocessing, 3- presence detection, 4- illumination compensation, 5- HD detection, and 6- heat detection. The proposed system will handle various image variations, and will be fast and cost-effective. The developed system will improve the productivity of Australian cattle industry.Read moreRead less
Multiview video coding using cuboid data compression. This project investigates novel approaches to multiview video coding that use new data compression techniques and explicit occlusion handling. These new approaches complement the state-of-the-art, improving interactivity with instantaneous view change and VCR functionality, reducing encoding complexity, and increasing compression efficiency.
Effective profiling of large scale combinatorial optimisation problems. Finding optimum solutions to problems is one of the most common challenges in planning. It pervades all aspects of our social, environmental and economic life. However, designing programs that can solve optimisation problems effectively requires an iterative process that is often extremely challenging, time consuming and costly. For large-scale problems, this process can become impractical. This project will investigate meth ....Effective profiling of large scale combinatorial optimisation problems. Finding optimum solutions to problems is one of the most common challenges in planning. It pervades all aspects of our social, environmental and economic life. However, designing programs that can solve optimisation problems effectively requires an iterative process that is often extremely challenging, time consuming and costly. For large-scale problems, this process can become impractical. This project will investigate methods to profile and understand program performance. The results will help users to design scalable, efficient optimisation programs. This will in turn allow organisations large and small to reap the benefits of optimisation technology and, thus, make more efficient use of their resources.Read moreRead less
Fruit shape estimation from stereoscopic images in real time. The research aims at improving the process of automatic fruit inspection and classification.
Existing stereo vision algorithms to extract depth information are unsuitable for real time calculations.
The increasing complexity and reducing cost of field programmable gate arrays along with the development of algorithms that have a high degree of parallelism and locality has created
the possibility of performing the calculation ....Fruit shape estimation from stereoscopic images in real time. The research aims at improving the process of automatic fruit inspection and classification.
Existing stereo vision algorithms to extract depth information are unsuitable for real time calculations.
The increasing complexity and reducing cost of field programmable gate arrays along with the development of algorithms that have a high degree of parallelism and locality has created
the possibility of performing the calculations required in real time.
This projects aims to investigate the suitability of the various stereo vision algorithms available in the literature for real time hardware implementation with application to fruit shape estimation it real time.
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Methodologies for face recognition under varying imaging conditions. Face recognition systems are heavily dependent on the nature of the input to the system. Variability in appearance due to changes in illumination, expression, pose, etc. can reduce the recognition results of the existing systems. The aim of this project is to develop new techniques to improve the recognition accuracy in natural environment where unwanted image variations exist. The development of such techniques will be of grea ....Methodologies for face recognition under varying imaging conditions. Face recognition systems are heavily dependent on the nature of the input to the system. Variability in appearance due to changes in illumination, expression, pose, etc. can reduce the recognition results of the existing systems. The aim of this project is to develop new techniques to improve the recognition accuracy in natural environment where unwanted image variations exist. The development of such techniques will be of great importance to Australia's security and safety. The outcome of this research will provide the first steps towards formulating the next generation recognition systems that will improve the suitability of the face recognition for use in security, surveillance, intelligent robotics, banking, and smart environments.Read moreRead less
Accurate analysis of combinatorial problems: from the particular to the general. Combinatorial problems pervade all aspects of our social, environmental and economic life, but finding good solutions to these problems can take too much computer time. This project will develop new analysis tools that are effective at reducing this time, thus allowing for better solutions to be found.