An efficient gradient computation approach to discriminative fusion optimization in semantic concept detection

Proceedings - International Conference on Pattern Recognition

Volumn , Issue , 2008, Pages

  Ma, Chengyuan ^a   Lee, Chin Hui ^a  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONTENT BASED RETRIEVAL; EXTRACTION; FEATURE EXTRACTION; SEMANTICS;

FUSION OPTIMIZATION; GRADIENT CALCULATIONS; GRADIENT COMPUTATION; HIGH-LEVEL FEATURE EXTRACTIONS; NUMERICAL APPROXIMATIONS; PERFORMANCE MEASURE; PERFORMANCE METRICS; SEMANTIC CONCEPT DETECTION;

COMPUTATIONAL EFFICIENCY;

EID: 77957944018     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/icpr.2008.4761471     Document Type: Conference Paper

References (13)

1. P. Over, T. Ianeva, W. Kraaij, and A. F. Smeaton. TRECVID 2005-an overview. Technical report, National Institute of Standards and Technology, 2005.
2. A. Yanagawa, S.-F. Chang, L. S. Kennedy, and W. Hsu. Columbia University's baseline detectors for 374 LSCOM semantic visual concepts. Technical report, Columbia University, 2007.
3. J. Yang, Y.-G. Jiang, A. G. Hauptmann, and C.-H. Ngo. Evaluating bag-of-visual-words representations in scene classification. In Proc. of ACMMIR, 2007.
4. B. Byun, C. Ma, and C.-H. Lee. An experimental study on discriminative concept classifier combination for TRECVID high-level feature extraction. submitted to ICIP 2008.
5. B. L. Tseng, C.-Y. Lin, M. Naphade, A. Natsev, and J. R. Smith. Normalized classifier fusion for semantic visual concept detection. In Proc. of ICIP, 2003.
6. Y. Aytar, O. B. Orhan, and M. Shah. Improving semantic concept detection and retrieval using contextual estimates. In Proc. of ICME, 2007.
7. T. Joachims. A support vector method for multivariate performance measures. In Proc. of ICML, 2005.
8. S. Gao, W. Wu, C.-H. Lee, and T.-S. Chua. A MFoM learning approach to robust multiclass multi-label text categorization. In Proc. of ICML, 2004.
9. S. Gao, C.-H. Lee, and J. H. Lim. An ensemble classifier learning approach to ROC optimization. In Proc. of ICPR, 2006.
10. X. Li, E. Chang, and B.-Q. Dai. Improving speaker verification with figure of merit training. In Proc. of ICASSP, 2002.
11. Y. Yue, T. Finley, F. Radlinski, and T. Joachims, A support vector method for optimizing average precision. In Proc. of SIGIR, 2007.
12. J. Davis and M. Goadrich. The relationship between precision-recall and roc curves. In Proc. of ICML, 2006.
13. L. Kennedy and A. Hauptmann. LSCOM lexicon definition and annotation version 1.0. Technical report, Columbia University, 2006.