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TAG: Parameter Estimation
Improved image analysis: maximised statistical use of geometry/shape constraints (DP130102524)
Prof. David Suter and Dr Tat-Jun Chin have been awarded a 3 year ARC Discovery Grant valued at $330,000. This project will improve image analysis to apply such applications as 3D street-scape reconstruction, synthetic inserts into video for special effects, autonomous navigation, and scene understanding. It will do so by maximally exploiting the geometry of […]
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Distributed Large-scale Optimization Methods in Computer Vision (DE130101775)
Dr Anders Eriksson of the ACVT has been awarded a 3 year ARC DECRA Fellowship valued at $375,000. Computer vision concerns itself with understanding the real world through the analysis of images. With the number of images and video available over the internet reaching several billions, and growing, this has begun to revolutionize the field. […]
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ACVT hosts model-fitting seminars, Monday 12th December 2011
On Monday 12th December, the ACVT welcomes two visitors: Professor Kenichi Kanatani, Professor of Computer Science at Okayama University, Japan, and Dr Andrew Comport, “Chargé de Recherches” (Tenure Researcher) with the Centre National de Recherche Scientifique (CNRS) in France. Along with Professor Wojciech Chojnacki, Senior Research Fellow in the School of Computer Science at The University […]
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DECRA Success! Congratulations to Dr Javen Shi
Well done to Javen who has been awarded $375,00o of DECRA funding through the ARC in the 2012 round!! Only 277 proposals were awarded from over 2,100 applications. This is a fabulous result for Javen, congratulations! Title: Compressive sensing based probabilistic graphical models (PGM) Project Summary: The aim of the project is to develop fast, large scale […]
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ACVT ARC Discovery Projects success
Profs David Suter and Anton van den Hengel were both awarded ARC Discovery Grants to begin in 2011. They are: Computer vision from a multi structural analysis framework, Prof D. Suter. Computer vision has applications in a wide variety of areas: security (video surveillance), entertainment (special effects), health care (medical imaging), and economy (improved automation and […]
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Computer vision from a multi-structural analysis framework (DP110103637)
Prof. David Suter has been awarded a 3 year ARC Discovery Grant valued at $300,000. Computer vision has applications in a wide variety of areas: security (video surveillance), entertainment (special effects), health care (medical imaging), and economy (improved automation and consumer products). This project will improve the accuracy and reliability of such applications. Advances will […]
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Robust Model Fitting
Numerous problems in Computer Vision can be reduced to fitting a generic model onto observed data or measurements. An example is identifying 2D shapes (e.g. lines, circles) in an image, where the model is a geometrical structure defined by a few parameters (e.g. slope and intercept, center and radius), and fitting the model onto the […]
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Visual tracking of multiple objects: A stochastic geometrical approach (DP0880553)
Prof. David Suter (Then of Monash University) along with Associate Prof. B Vo has been awarded a 3 year ARC Discovery Grant valued at $235,000. Reliable real-time visual multiple-object tracking techniques will open up new applications that enhance the quality of life such as driving safety, traffic monitoring, home security, security and surveillance of public […]
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Statistical Methods of Model Fitting and Segmentation in Computer Vision (DP0878801)
Prof. David Suter (then of Monash University) and Professor A Bab-Hadiashar have been awarded a 4 year ARC Discovery Grant valued at $422,000. 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, […]
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