Laplacian adaptive context-based SVM for video concept detection

MM'11 - Proceedings of the 2011 ACM Multimedia Conference and Co-Located Workshops - WSM'11: 3rd ACM Social Media Workshop

Volumn , Issue , 2011, Pages 15-20

  Jiang, Wei ^a   Loui, Alexander C ^a  

^a EASTMAN KODAK COMPANY   (United States)

Author keywords

Active annotation; Cross domain; Semantic concept detection

Indexed keywords

A-LAPLACIAN; ACTIVE ANNOTATION; ACTIVE LEARNING; CONCEPT DETECTION; CONTEXT-BASED; CROSS-DOMAIN; DETECTION ACCURACY; LABELED TRAINING DATA; LAPLACIANS; MANUAL ANNOTATION; SEMANTIC CONCEPT DETECTION; SEMI-SUPERVISED LEARNING; STATE-OF-THE-ART METHODS; TARGET DOMAIN; TEST DATA; TWO-DIMENSION; UNLABELED DATA; VIDEO CONCEPT DETECTION;

LAPLACE TRANSFORMS; SEMANTICS; SUPERVISED LEARNING;

VIDEO STREAMING;

EID: 84855361719     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2072609.2072615     Document Type: Conference Paper

References (18)

1. M. Belkin, P. Niyogi, and V. Sindhwani, Manifold regularization: a geometric framework for learning from labeled and unlabeled examples. Journal of Machine Learning Research, 7(11):2399-2434, 2006. (Pubitemid 44708005)
2. S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge University Press, Cambridge, 2004.
3. S. Chang, D. Ellis, W. Jiang, K. Lee, A. Yanagawa, A. Loui, and J. Luo. Large-scale multimodal semantic concept detection for consumer video. In Proc. ACM MIR, pages 255-264, 2007.
4. O. Chapelle, B. Scholkopf, and A. Ziene. Semi-supervised Learning. MIT Press, Cambridge, MA, 2006.
5. H. Daumé. Frustratingly easy domain adaptation. In Proc. the 45th Annual Meeting of the Association of Computational Linguistics, pages 256-263, 2007.
6. L. Duan, I. Tsang, D. Xu, and S.J. Maybank. Domain transfer svm for video concept detection. In IEEE CVPR, pages 1375-1381, 2009.
7. W. Jiang, S. Chang, and A. Loui. Active context-based concept fusion with partial user labels. In IEEE ICIP, pages 2917-2920, 2006.
8. W. Jiang, E. Zavesky, S. Chang, and A. Loui. Cross-domain learning methods for high-level visual concept classification. In IEEE ICIP, 2008.
9. Y. Jiang, J. Wang, S. Chang, and C.W. Ngo. Domain adaptive semantic diffusion for large scale context-based video annotation. In IEEE ICCV, 2009.
10. Y. Jiang, G. Ye, S. Chang, D. Ellis, and A. Loui. Consumer video understanding: A benchmark database and an evaluation of human and machine performance. In ACM ICMR, 2011. Trento, Italy.
11. A. Loui, J. Luo, S. Chang, D. Ellis, W. Jiang, L. Kennedy, K. Lee, and A. Yanagawa. Kodak's consumer video benchmark data set: Concept definition and annotation. ACM MIR, 2007.
12. M. Newman. Mathematics of Networks. The New Palgrave Encyclopedia of Economics, 2nd Edition, L.E. Blume and S.N. Durlauf (eds.), Palgrave Macmillan, Basingstoke, 2008.
13. G. Qi and et al. Correlative multi-label video annotation. In ACM Multimedia, pages 17-26, 2007.
14. G. Qi, X.S. Hua, Y. Rui, J. Tang, and H.J. Zhang. Two-dimensional active learning for image classification. In IEEE CVPR, pages 1-8, 2008.
15. A.F. Smeaton, P. Over, and W. Kraaij. Evaluation campaigns and TRECVid. ACM MIR, 2006.
16. S. Tong and E. Chang. Support vector machine active learning for image retrieval. In ACM Multimedia, 2001.
17. V. Vapnik. Statistical Learning Theorys. Wiley-Interscience, New York, 1998.
18. J. Yang, R. Yan, and A. Hauptmann. Cross-domain video concept detection using adaptive svms. In ACM Multimedia, pages 188-197, 2007.