Global Utilities

Research Publications - Abstract

Department of Computer Science & Computer Engineering

Wang, D., and Conilione, P.
Publication Year: 2009
Paper Title: Intelligent Face Image Retrieval Using Eigenpaxels and Learning Similiarity Metrics
Conference Name: 15th International Conference on Neural Information Processing, ICONIP 2008
Venue: Aukland, New Zealand
Volume: LNCS 5507, Part II, 2009
Pages: 792 - 799
Abstract: Content-based Image Retrieval (CBIR) systems have been rapidly developing over the years, both in labs and in real world applications. Face Image Retrieval (FIS ) is a specialised CBIR system where a user submits a query (image of a face) to the FIR system which searches and retrieves the most visually similar face images from a database. In this paper, we use a neural-network based similarity measure and compare the retrieval performance to Lp-norm similarity measures. Further we examined the effect of user relevance-feedback on retrieval performance. It was found that the neural-similarity measure provided significant performance gains over Lp-norm similarity measure for both the training and test data sets.
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Last Updated: 14 October, 2009