Towards automatic feature vector optimization for multimedia applications

Authors:
Tobias Schreck;Dieter Fellner;Daniel Keim
Affiliations:
TU Darmstadt Fraunhoferstrasse, Darmstadt, Germany;Fraunhofer IGD and TU Darmstadt Fraunhoferstrasse, Darmstadt, Germany;University of Konstanz Universitaetsstr, Konstanz, Germany
Venue:
Proceedings of the 2008 ACM symposium on Applied computing
Year:
2008

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Abstract

We systematically evaluate a recently proposed method for unsupervised discrimination power analysis for feature selection and optimization in multimedia applications. A series of experiments using real and synthetic benchmark data is conducted, the results of which indicate the suitability of the method for unsupervised feature selection and optimization. We present an approach for generating synthetic feature spaces of varying discrimination power, modeling main characteristics from real world feature vector extractors. A simple, yet powerful visualization is used to communicate the results of the automatic analysis to the user.