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TUB @ MediaEval 2012 Tagging Task: Feature Selection Methods for Bag-of-(visual)-Words Approaches
Citation key 1386Schmiedeke2012
Author Sebastian Schmiedeke and Pascal Kelm and Thomas Sikora
Title of Book Working Notes Proceedings of the MediaEval 2012 Workshop
Pages 79–80
Year 2012
Address Santa Croce in Fossabanda Piazza Santa Croce, 5 - 56125 - Pisa - Toscana - Italia
Month oct
Note ISSN 1613-0073
Editor Martha A. Larson, Sebastian Schmiedeke, Pascal Kelm, Adam Rae, Vasileios Mezaris, Tomas Piatrik, Mohammad Soleymani, Florian Metze, Gareth J.F. Jones
Publisher CEUR-WS.org
Abstract This paper describes our participation in the Genre Tagging Task of MediaEval 2012, which aims to predict the videos’ category label. In last year’s participation, we performed experiments with bag-of-words (BoW) approaches in which different constellations in respect of modalities, features, and methods were investigated. This year, we focus on feature selection methods to improve the classification performance in terms of mean average precision (mAP) and classification accuracy (CA). We investigated the effectiveness of selection methods based on scores calculated using mutual informa- tion (MI) or term frequency (TF) and the effectiveness of transformation methods like the principle component anal- ysis (PCA).
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