| Title: |
An Empirical Study Of Multi-Label Learning Methods For Video Annotation |
| Author(s): |
A. Dimou, G. Tsoumakas, V. Mezaris, I. Kompatsiaris, I. Vlahavas.
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| Availability: |
Click here to download the PDF (Acrobat Reader) file (6 pages).
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| Keywords: |
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| Appeared in: |
7th International Workshop on Content-Based Multimedia Indexing, IEEE, Chania, Crete, 2009.
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| Abstract: |
This paper presents an experimental comparison of different approaches to learning from multi-labeled video data. We compare state-of-the-art multi-label learning methods on
the Mediamill Challenge dataset. We employ MPEG-7 and SIFT-based global image descriptors independently and in conjunction using variations of the stacking approach for
their fusion. We evaluate the results comparing the different classifiers using both MPEG-7 and SIFT-based descriptors and their fusion. A variety of multi-label evaluation measures
is used to explore advantages and disadvantages of the examined classifiers. Results give rise to interesting conclusions. |
| See also : |
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This paper has been cited by the following:
| 1 |
M. Antenreiter, R. Ortner, and P. Auer, “Combining Classifiers for Improved Multilabel Image Classification”, Proceedings of the ECML/PKDD 2009 Workshop on Learning from Multi-Label Data (MLD’09), pp. 16-27, Bled, Slovenia, September 2009. |
| 2 |
Huo,Y. (2010) Multi-label image categorization for general concepts using bag of words model, MSc Thesis, Leiden Institute of Advanced Computer Science |
| 3 |
Nasierding, G., Kouzani, A.Z. (2010) "Empirical Study of Multi-label Classification Methods for Image Annotation and Retrieval," dicta, pp.617-622, 2010 International Conference on Digital Image Computing: Techniques and Applications.
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| 4 |
Gold, K., Petrosino, A. (2010) Using Information Gain to Build Meaningful Decision Forests for Multilabel Classification. To be presented at ICDL 2010, Ann Arbor, Michigan.
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| 5 |
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| 7 |
Muhammad Tahir, Josef Kittler, Krystian Mikolajczyk, and Fei Yan. "Improving multilabel classification performance by using ensemble of multi-label classifiers". In Neamat Gayar, Josef Kittler, and Fabio Roli, editors, Multiple Classifier Systems, volume 5997, chapter 2, pages 11–21. Springer Berlin Heidelberg, Berlin, Heidelberg, 2010. |
| 8 |
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| 11 |
Briggs,F.;Lakshminarayanan,B.;Neal,L.;Fern,X.Z.;Raich,R.;Hadley,S.J.K.;Hadley,A.S.;Betts,M.G. (2012) Acoustic classification of multiple simultaneous bird species: A multi-instance multi-label approach, J. Acoust. Soc. Am. 131, 4640.
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