Braving the semantic gap: mapping visual concepts from images and videos

Authors:
Da Deng
Affiliations:
Department of Information Science, University of Otago, New Zealand
Venue:
ICDM'04 Proceedings of the 4th international conference on Advances in Data Mining: applications in Image Mining, Medicine and Biotechnology, Management and Environmental Control, and Telecommunications
Year:
2004

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Abstract

A set of feature descriptors have been proposed and rigorously in the MPEG-7 core experiments. We propose to extend the use of these descriptors onto semantics extraction from images and videos, so as to bridge the semantic gap in content-based image retrieval and enable multimedia data mining on semantics level. A computational framework consisting of a clustering process for feature mapping and a classification process for object extraction is introduced. We also present some preliminary results obtained from the experiments we have conducted.