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Surveillance Patent granted

The US patent office has granted the patent which covers the large-scale surveillance technology being commercialised by SNAP Surveillance. This is great news for SNAP, but also for the ACVT.  It’s US Patent number 8396250.

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2011 Pearcey SA Entrepreneur Award – Runner Up

Congratulations to Dr Henry Detmold who was Runner Up in the 2011 Pearcey SA Entrepreneur Award! The Entrepreneur Award is a State award, rolling up into the Benson National ICT Entrepreneur of the Year Award, and is aimed at encouraging and rewarding fresh and innovative talent in the ICT and Digital Media professions Henry was awarded a special […]

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Content Based Image Retrieval

The World Wide Web is a visual place, full of images and video. As of September 2010, Flickr hosts over 5 billion photos, while over 2 billion videos are watched every day on Youtube. This is a vast store of information, but how can we find what we want? Currently, images are almost always identified […]

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Large-Scale Intelligent Video Surveillance

A key step towards automating the monitoring of video from many cameras is to generate an understanding of the paths which targets may take between their fields of view. This activity topology information is the foundation for many fundamental tasks in networked surveillance, such as tracking an object across the network. Although it could be […]

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ACVT members win grant for Large Scale Video Surveillance

Congratulations to Anton van den Hengel, David Suter, Anthony Dick, and Henry Detmold, who were recently awarded a major grant for ‘Accelerating Australia’s large scale video surveillance research programmes': The research to be conducted using this infrastructure will bring immense benefits to Australia in terms of increased levels of public safety and in the protection […]

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Accelerating Australia’s Large Scale Video Surveillance Research Programmes (LE100100235)

ACVT has been awarded an ARC LIEF Grant valued at $280,000 to acquire equipment and infrastructure to support research in large scale video surveillance. The CIs include Prof. Anton van den Hengel, Prof. David Suter, Prof. Mike Brooks, Dr Anthony Dick, Dr Henry Detmold and Dr Chunhua Shen. This project will construct a world-class video […]

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ACVT wins CTD

The ACVT has been successful in attracting a Capability and Technology Demonstrator (CTD) Program award from the Federal Government and DSTO. The award supports the development of a technology demonstrator based on ACVT’s existing capabilities in in content-based image retrieval. Content-based image retrieval allows large image databases to be searched on the basis of the images themselves. It means that […]

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Tracking targets in large scale surveillance camera networks (DP1094764)

ACVT has been awarded a 3 year ARC Discovery Grant valued at $195,000. The CIs are Dr Anthony Dick, Dr Henry Detmold. Dr Philip Torr of Oxford Brookes University in the UK is also a CI. Surveillance camera networks in public places such as airports and shopping malls may contain thousands of cameras. However, state […]

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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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The Australian Centre for Visual Technologies
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Level 5, Ingkarni Wardli,
The University of Adelaide,
North Terrace,
Adelaide, 5005

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