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Poster Submissions
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Distributed Grid Computing for Multi-million Image Retrieval
Christopher Town, University of Cambridge and Imense Ltd.
Further information: www.cl.cam.ac.uk/~cpt23, www.imense.com |
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Imense Ltd has implemented a new kind of image retrieval system based on automated analysis and recognition of image content. The system does not rely on image annotations or metadata, and does not require an initial example image or sketch to be supplied by the user. Instead, it features a range of image processing and analysis modules which can automatically recognise semantic image content. However, with an estimated 15 billion images available on the internet today, there is great need for technologies to provide the scalable computing resources required to process such vast quantities of data. With the help of funding from the UK STFC and in collaboration with the Cambridge University eScience Centre, we are developing techniques for analysing millions of images using grid processing technology. We have ported our software to the middleware architecture deployed on the UK particle physics grid and have processed several million images to date. We are also furthering middleware and user interface development to make it easier for non-physics applications from academia or industry to make use of grid computing. |
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