Peter HowarthVisiting Researcher
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.
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.
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
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
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., Howarth, P., Magalhães, J., May, A., Pickering, M., Yavlinsky, A. and Rueger, S. (2004) Video retrieval using search and browsing, TREC Video Retrieval Evaluation, Gaithersburg, MD