2 post docs positions - Oxford Brookes University, UK

2 post docs positions - Oxford Brookes University, UK

Posted by Rebecca Martin on Fri, 05/08/2011 - 09:03

Two 2 year research fellowship to work with Philip Torr at Oxford Brookes vision research group http://cms.brookes.ac.uk/research/visiongroup/.

You will engage in state-of-the-art research in computer vision. In particular the work will be an EPSRC & Google grants on “Scene Understanding using New Global Energy Models”. To work on recognizing and reconstructing street view imagery, experts sought in SLAM, energy minimization and recognition!

The vision group at Oxford Brookes has won numerous awards including paper prizes at ECCV, CVPR, NIPS, BMVC and ICCV, and has strong connections internationally with academia and industry.

This proposal concerns scene understanding from video. Computer vision algorithms for individual tasks such as object recognition, detection and segmentation has now reached some level of maturity. The next challenge is to integrate all these algorithms and address the problem of scene understanding. The problem of scene understanding involves explaining the whole image by recognizing all the objects of interest within an image and their spatial extent or shape in 3D.

The first application to drive the research will be the problem of automated understanding of cities from video using computer vision, inspired by the availability of massive new data sets such as that of Google’s Street View http://maps.google.com/help/maps/streetview/
, Yotta http://www.yotta.tv/index.php
(who have agreed to supply Oxford Brookes with data) and Microsoft’s Photosynth http://labs.live.com/photosynth/
. The scenario is as follows: a van drives around the roads of the UK, in the van are GPS equipment and multiple calibrated cameras, synchronized to capture and store an image every two metres; giving a massive data set. The task is to recognize objects of interest in the video, from road signs and other street furniture, to particular buildings, to allow them to be located exactly on maps of the environment. A second scenario would be to perform scene understanding for indoor scenes such as home or office, with video taken from a normal camera and Z-cam.

For further information contact philiptorr(at)brookes.ac.uk

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