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Proceedings Paper

Evaluation of content-based features for user-centered image retrieval in small media collections
Author(s): Horst Eidenberger; Maia Zaharieva
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Paper Abstract

The experiments described in this paper indicate that under certain conditions content-based features are not required for efficient user-centred image retrieval in small media collections. The importance of feature selection drops dramatically if classification is used for retrieval (e.g. if Support Vector Machines are used) and only little user feedback is available. In this situation simple image features and even random features perform equally well as sophisticated signal processing-based features (e.g. the content-based MPEG-7 image descriptors). Practically relevant applications for these findings are retrieval on mobile devices and in heterogeneous (e.g. ad hoc generated) media collections.

Paper Details

Date Published: 28 January 2008
PDF: 12 pages
Proc. SPIE 6820, Multimedia Content Access: Algorithms and Systems II, 68200J (28 January 2008); doi: 10.1117/12.753725
Show Author Affiliations
Horst Eidenberger, Vienna Univ. of Technology (Austria)
Maia Zaharieva, Vienna Univ. of Technology (Austria)

Published in SPIE Proceedings Vol. 6820:
Multimedia Content Access: Algorithms and Systems II
Theo Gevers; Ramesh C. Jain; Simone Santini, Editor(s)

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