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Alexei Yavlinsky Photograph

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Alexei was a 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.

His thesis http://people.kmi.open.ac.uk/stefan/www-pub/a.yavlinsky-phd.pdf Image

indexing and retrieval using automated annotation, published in 2007,

argues that models of simple image features, such as global colour and

texture, can be used to predict instances of different objects and scenes

within photographic images. On this basis Alexei proposed the use of

nonparametric density estimation to model these features and thus endow

unlabelled images with probabilities of containing particular objects and

scenes. This process, termed automated image annotation, enables one to

set up a scalable image indexing framework that allows users to retrieve

unlabelled images from large collections using simple keyword queries.

Keys: mmis

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Publications

Publications | Visit External Site for Details Publications | doi 

Yavlinsky, A. and Rueger, S. (2007) Efficient re-indexing of automatically annotated image collections using keyword combination, Multimedia Content Analysis, Management and Retrieval (SPIE), San Jose, CA Proc Multimedia Content Analysis, Management and Retrieval

 

, Overell, S., Yavlinsky, A. and Rueger, S. (2006) Imperial College at TRECVID, TREC Video Retrieval Evaluation, Gaithersburg, MD

 

Ghoshal, A., Khudanpur, S., Magalhaes, J., Overell, S., Rueger, S. and Yavlinsky, A. (2006) Imperial College and Johns Hopkins University at TRECVID, TREC Video Retrieval Evaluation, Gaithersburg, Maryland, USA

Publications | Visit External Site for Details Publications | doi 

Heesch, D., Yavlinsky, A. and Rueger, S. (2006) NNk networks and automated annotation for browsing large image collections from the world wide web, Proceedings of the 14th annual ACM international conference on Multimedia, Santa Barbara, CA, USA

 

Yavlinsky, A., Heesch, D. and Rueger, S. (2006) A large scale system for searching and browsing images from the World Wide Web, International Conference on Image and Video Retrieval, Tempe, AZ LNCS 4071, pp. 537-540, Springer

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