IRIM at TRECVID2009: High Level Feature Extraction

Abstract : The IRIM group is a consortium of French teams working on Multimedia Indexing and Retrieval. This paper describes our participation to the TRECVID 2009 High Level Features detection task. We evaluated a large number of different descriptors (on TRECVID 2008 data) and tried different fusion strategies, in particular hierarchical fusion and genetic fusion. The best IRIM run has a Mean Inferred Average Precision of 0.1220, which is significantly above TRECVID 2009 HLF detection task median performance. We found that fusion of the classification scores from different classifier types improves the performance and that even with a quite low individual performance, audio descriptors can help.
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Communication dans un congrès
TREC Video Retrieval Evaluation: TRECVID, Nov 2009, Gaithersburg, MD, United States. TREC Video Retrieval Evaluation Online Proceedings (TRECVID), 2010
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https://hal.archives-ouvertes.fr/hal-00468199
Contributeur : Boris Mansencal <>
Soumis le : mardi 30 mars 2010 - 12:14:54
Dernière modification le : vendredi 3 février 2017 - 10:55:37
Document(s) archivé(s) le : jeudi 1 juillet 2010 - 20:25:41

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IRIMatTRECVID2009.pdf
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  • HAL Id : hal-00468199, version 1

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Bertrand Delezoide, Hervé Le Borgne, Pierre-Alain Moëllic, David Gorisse, Frédéric Precioso, et al.. IRIM at TRECVID2009: High Level Feature Extraction. TREC Video Retrieval Evaluation: TRECVID, Nov 2009, Gaithersburg, MD, United States. TREC Video Retrieval Evaluation Online Proceedings (TRECVID), 2010. <hal-00468199>

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