Columbia University TRECVID2007 high-level feature extraction

2007 TREC Video Retrieval Evaluation Notebook Papers

Volumn , Issue , 2007, Pages

  Chang, Shih Fu ^a   Jiang, Wei ^a   Yanagawa, Akira ^a   Zavesky, Eric ^a  

^a Columbia University Department of Electrical Engineering ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING SYSTEMS;

COLUMBIA UNIVERSITY; COMPARATIVE STUDIES; COMPUTATIONAL COSTS; CONTRIBUTING FACTOR; CROSS-DOMAIN LEARNING; HIGH-LEVEL FEATURE EXTRACTIONS; PREDICTION MECHANISMS; SELECTION CRITERIA;

FEATURE EXTRACTION;

EID: 84905196551     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. S.F. Chang, et al., "Columbia University TRECVID-2005 Video Search and High-Level Feature Extraction". In NIST TRECVID workshop, Gaithersburg, MD, 2005.
2. S.F. Chang, et al., "Columbia University TRECVID-2006 Video Search and High-Level Feature Extraction". In NIST TRECVID workshop, Gaithersburg, MD, 2006.
3. C.C. Chang and C.J. Lin, "LIBSVM: a library for support vector machines", http://www.csie.ntu.edu.tw/ cjlin/libsvm, 2001.
4. Y. Chen, et al., "Learning with progressive transductive support vector machines", IEEE Intl. Conf. on Data Mining, 2002.
5. H.B. Cheng, et al., "Localized support vector machine and its efficient algorithm", Proc. SIAM Intl' Conf. Data Mining, 2007.
6. Hsu, W., et al. "Discovery and Fusion of Salient Multi-modal Features towards News Story Segmentation". In IS&T/SPIE Symposium on Electronic Imaging: Science and Technology-SPIE Storage and Retrieval of Image/Video Database. 2004. San Jose, USA.
7. Caruana, R., et al., "Ensemble selection from libraries of models" Proceedings of the Twenty-First International Conference on Machine Learning 2004. ACM Press: Banff, Alberta, Canada p. 18.
8. H. Daumé III, "Frustratingly easy domain adaptation", Proc. the 45th Annual Meeting of the Association of Computational Linguistics, 2007.
9. A. Gammerman, et al., "Learning by transduction", Conf. Uncertainty in Artificial Intelligence, pp.148-156, 1998.
10. W. Jiang, E. Zavesky, S.-F. Chang, A. Loui, "Cross-domain Learning Methods for High-level Visual Concept Classification", submitted IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Las Vegas, USA, April 2008.
11. W. Jiang, S.-F. Chang, and A. C. Loui. "Context-based Concept Fusion with Boosted Conditional Random Fields". IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Hawaii, USA, April 2007.
12. M. R. Naphade, et al., "A Light Scale Concept Ontology for Multimedia Understanding for TRECVID 2005, " IBM Research Technical Report, 2005.
13. Stphane Ayache and Georges Qunot, "Evaluation of active learning strategies for video indexing", In Fifth International Workshop on Content-Based Multimedia Indexing (CBMI'07), Bordeaux, France, June 25-27, 2007.
14. Smeaton, A. F., Over, P., and Kraaij, W. 2006. "Evaluation campaigns and TRECVid. " In Proceedings of the 8th ACM International Workshop on Multimedia Information Retrieval. Santa Barbara, California, USA, October 26-27, 2006.
15. V. Vapnik and C. Cortes, "Support vector network", Machine Learning, vol.20, pp.273-297, 1995.
16. Akira Yanagawa, Shih-Fu Chang, Lyndon Kennedy, Winston Hsu. "Columbia University's Baseline Detectors for 374 LSCOM Semantic Visual Concepts". Research Report Columbia University, March 2007.
17. J. Yang, et al., "Cross-domain video concept detection using adaptive svms", ACM Multimedia, 2007.
18. Zhu Liu and David Gibbon and Behzad Shahraray, "Multimedia Content Acquisition and Procesing in the MIRACLE system, " CCNC 2006, Las Vegas, Jan. 8-10, 2006.