Full-time Postgraduate Research Studentship – visual annotation in content-based search Knowledge Media Institute

Based in Milton Keynes, Tenable from 1 October 2007

The project aims to develop effective methods for automatic annotation of visual content by text labels so as to enhance content-based search as well as integrate with traditional text-based search engines. The main research issues include the best choice of content features for particular types of visual search, novel and efficient ways of generating automated visual annotations from pixels that are computationally simple, and how to combine evidence from various sources. This project will be carried out in the context of the new PHAROS project, which is a main Integrated Project funded by the EU FP6. The methods developed from this PhD project will be plugged into the FAST search engine and will be evaluated using standard datasets from evaluation conferences such as TRECvid and ImageCLEF etc., and data from PHAROS content providers.

You should have a strong background in Computer Science or Information Systems, and must have qualifications of First or upper second class honours degree or research master degree. Strong programming skills in C/C++ and Matlab, existing research experience in computer vision,
human-computer-interaction or information retrieval, and international conference/journal publications would be desirable. This studentship is open for national and international applicants.

The studentship rate is £12,600 a year.

For further information, and to apply go to:http://kmi.open.ac.uk/studentships/studentship3.cfm or contact Professor Stefan Rüger [*s.rueger@open.ac.uk*] or Dr. Dawei Song [d.song@open.ac.uk], quoting the reference code: 2714.

Closing date: 10 June 2007.