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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Semi-supervised Concept Detection by Learning the Structure of Similarity Graphs
verfasst von : Symeon Papadopoulos, Christos Sagonas, Ioannis Kompatsiaris, Athena Vakali
Erschienen in: Advances in Multimedia Modeling
Verlag: Springer Berlin Heidelberg
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We present an approach for detecting concepts in images by a graph-based semi-supervised learning scheme. The proposed approach builds a similarity graph between both the labeled and unlabeled images of the collection and uses the Laplacian Eigemaps of the graph as features for training concept detectors. Therefore, it offers multiple options for fusing different image features. In addition, we present an incremental learning scheme that, given a set of new unlabeled images, efficiently performs the computation of the Laplacian Eigenmaps. We evaluate the performance of our approach both on synthetic datasets and on MIR Flickr, comparing it with high-performance state-of-the-art learning schemes with competitive and in some cases superior results.