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.
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
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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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
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.
How feedback can impair recognition judgments and undermine border security, criminal investigations, educational testing, and medical screening. If a customs officer learns that they have missed an explosive device while screening luggage, will this affect their judgment? In many scenarios, a person receives feedback about their recognition memory performance and has to try again without having another chance to study the material. Almost no research has examined the effects of feedback on reco ....How feedback can impair recognition judgments and undermine border security, criminal investigations, educational testing, and medical screening. If a customs officer learns that they have missed an explosive device while screening luggage, will this affect their judgment? In many scenarios, a person receives feedback about their recognition memory performance and has to try again without having another chance to study the material. Almost no research has examined the effects of feedback on recognition in the absence of opportunity for further study. This is problematic because many vitally important recognition decisions lack such opportunity. Using various scenarios (face recognition, security screening, multiple-choice testing, and medical screening) this project will demonstrate that feedback affects recognition performance differently depending on the nature of the recognition decision.Read moreRead less
Optimal strategies for collaborative visual search. The ability of individual operators to search for and detect targets is a weak link in many military, medical, and industrial operations. Teams of operators, however, can perform well even when individuals do not. This project aims to investigate a promising new eye-tracking technique, gaze-linking, that helps searchers collaborate efficiently by allowing each to know where the other is looking. This research builds on mathematical models of in ....Optimal strategies for collaborative visual search. The ability of individual operators to search for and detect targets is a weak link in many military, medical, and industrial operations. Teams of operators, however, can perform well even when individuals do not. This project aims to investigate a promising new eye-tracking technique, gaze-linking, that helps searchers collaborate efficiently by allowing each to know where the other is looking. This research builds on mathematical models of information processing to identify strategies that optimise gaze-linked collaboration, and is expected to develop principles for training gaze-linked searchers. Gaze-linking offers a promising, and potentially economical, technique for improving human performance, increasing efficiency and safety in a variety of tasks.Read moreRead less
Developing a generative transformational theory of visual perception. This project will develop and test a generative, transformational computer model of visual perception, based on fractal encoding. This uses a powerful similarity metric to select transformations, that, when applied to image elements, generate a replica of the image. The model can detect and analyse structure in regular and semi-regular images, even when embedded in noise. This approach provides an explanation for several perce ....Developing a generative transformational theory of visual perception. This project will develop and test a generative, transformational computer model of visual perception, based on fractal encoding. This uses a powerful similarity metric to select transformations, that, when applied to image elements, generate a replica of the image. The model can detect and analyse structure in regular and semi-regular images, even when embedded in noise. This approach provides an explanation for several perceptual phenomena and illusions. It can reconcile opposed theories of perception and provide a unifying perspective on perception and cognition. Practical applications include the automatic recognition of objects in imagery and the detection of structure in complex data.Read moreRead less
Developing an integrative theoretical account of some basic mechanisms and limiting factors in human perception and cognition. The principal factors limiting cognitive performance are widely considered to be information processing speed, working memory capacity, and the effective control of cognitive processes. The proposed programme aims to develop and test a unifying theory relating these to two of the most basic achievements of the brain - discrimination and identification. This will help us ....Developing an integrative theoretical account of some basic mechanisms and limiting factors in human perception and cognition. The principal factors limiting cognitive performance are widely considered to be information processing speed, working memory capacity, and the effective control of cognitive processes. The proposed programme aims to develop and test a unifying theory relating these to two of the most basic achievements of the brain - discrimination and identification. This will help us to understand the underlying basis of differences and changes in cognitive performance. The outcomes have implications for the design, analysis and interpretation of studies of perception, judgement, memory and intelligence. The research also has applied relevance to neuropsychology, information handling and the design of system interfaces.Read moreRead less