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Peter Howarth (Alumni) Member status icon

Visiting Researcher
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Peter was a full-time PhD student in information retrieval at the

Department of Computing, Imperial College London, in the Multimedia and

Information Systems Group, supervised by Prof Stefan Rueger.

Peter's thesis

http://people.kmi.open.ac.uk/stefan/www-pub/p.howarth-phd.pdf Discovering

images: features, similarities and subspaces, published in 2007,

investigates three of the core components of content-based image

retrieval: visual features, similarity functions and indexing methods. In

the content-based paradigm images are searched in a purely visual domain,

where they are represented by high-dimensional features. Exhaustively

searching this feature space can take a prohibitively long time. The

thesis argues that by the use of judicious approximations we can search

large collections interactively, while keeping a good level of retrieval

performance. Using normal hardware, Peter's system was able to search four

million images in just over one second, thus satisfying the goal of

effective real-time searching of large image collections.

Peter joined Redington Partners, London, after his PhD research.

Keys: mmis




Howarth, P. and Rueger, S. (2005) Trading Precision for Speed: Localised Similarity Functions, International Conference on Image and Video Retrieval, Singapore International Conference on Image and Video Retrieval, pp. 415-424, Springer


Howarth, P. and Rueger, S. (2005) Fractional Distance Measures for Content-Based Image Retrieval, European Conference on Information Retrieval, Santiago de Compostela, Spain 27th European Conference on Information Retrieval, pp. 447-456, Springer

Publications | Visit External Site for Details  

Howarth, P. and Rueger, S. (2005) Robust texture features for still-image retrieval, IEE Proceedings on Vision, Image and Signal, 152, 6, pp. 868-874

Publications | Visit External Site for Details  

Howarth, P., Yavlinsky, A., Heesch, D. and Rueger, S. (2005) Medical Image Retrieval using Texture, Locality and Colour, Cross Language Evaluation Forum Lecture Notes from the Cross Language Evaluation Forum, pp. 740-749, Springer


Heesch, D., (2004) Video retrieval using search and browsing, TREC Video Retrieval Evaluation, Gaithersburg, MD

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