The University of Amsterdam’s Concept Detection System at ImageCLEF 2009 View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2010

AUTHORS

Koen E. A. van de Sande , Theo Gevers , Arnold W. M. Smeulders

ABSTRACT

Our group within the University of Amsterdam participated in the large-scale visual concept detection task of ImageCLEF 2009. Our experiments focus on increasing the robustness of the individual concept detectors based on the bag-of-words approach, and less on the hierarchical nature of the concept set used. To increase the robustness of individual concept detectors, our experiments emphasize in particular the role of visual sampling, the value of color invariant features, the influence of codebook construction, and the effectiveness of kernel-based learning parameters. The participation in ImageCLEF 2009 has been successful, resulting in the top ranking for the large-scale visual concept detection task in terms of both EER and AUC. For 40 out of 53 individual concepts, we obtain the best performance of all submissions to this task. For the hierarchical evaluation, which considers the whole hierarchy of concepts instead of single detectors, using the concept likelihoods estimated by our detectors directly works better than scaling these likelihoods based on the class priors. More... »

PAGES

261-268

References to SciGraph publications

Book

TITLE

Multilingual Information Access Evaluation II. Multimedia Experiments

ISBN

978-3-642-15750-9
978-3-642-15751-6

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-15751-6_32

DOI

http://dx.doi.org/10.1007/978-3-642-15751-6_32

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1005081003


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