메뉴 건너뛰기




Volumn , Issue , 2014, Pages 297-304

Zero-example event search using MultiModal Pseudo Relevance Feedback

Author keywords

0Ex; MED; Multimedia event detection; MultiModal pseudo relevance feedback; PRF; Zero example

Indexed keywords

SEMANTICS;

EID: 84899746163     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2578726.2578764     Document Type: Conference Paper
Times cited : (56)

References (32)
  • 3
    • 57349144427 scopus 로고    scopus 로고
    • Selecting good expansion terms for pseudo-relevance feedback
    • G. Cao, J. Y. Nie, J. Gao, and S. Robertson. Selecting good expansion terms for pseudo-relevance feedback. In SIGIR, pages 243-250, 2008.
    • (2008) SIGIR , pp. 243-250
    • Cao, G.1    Nie, J.Y.2    Gao, J.3    Robertson, S.4
  • 4
    • 84889607930 scopus 로고    scopus 로고
    • Zero-shot video retrieval using content and concepts
    • J. Dalton, J. Allan, and P. Mirajkar. Zero-shot video retrieval using content and concepts. In CIKM, pages 1857-1860, 2013.
    • (2013) CIKM , pp. 1857-1860
    • Dalton, J.1    Allan, J.2    Mirajkar, P.3
  • 6
    • 34547226504 scopus 로고    scopus 로고
    • Video search reranking via information bottleneck principle
    • W. H. Hsu, L. S. Kennedy, and S.-F. Chang. Video search reranking via information bottleneck principle. In Multimedia, pages 35-44, 2006.
    • (2006) Multimedia , pp. 35-44
    • Hsu, W.H.1    Kennedy, L.S.2    Chang, S.-F.3
  • 7
    • 84883075039 scopus 로고    scopus 로고
    • Joint visual-text modeling for automatic retrieval of multimedia documents
    • G. Iyengar, P. Duygulu, S. Feng, P. Ircing, S. Khudanpur, et al. Joint visual-text modeling for automatic retrieval of multimedia documents. In Multimedia, pages 21-30, 2005.
    • (2005) Multimedia , pp. 21-30
    • Iyengar, G.1    Duygulu, P.2    Feng, S.3    Ircing, P.4    Khudanpur, S.5
  • 8
    • 84871359352 scopus 로고    scopus 로고
    • Leveraging high-level and low-level features for multimedia event detection
    • L. Jiang, A. G. Hauptmann, and G. Xiang. Leveraging high-level and low-level features for multimedia event detection. In Multimedia, pages 449-458, 2012.
    • (2012) Multimedia , pp. 449-458
    • Jiang, L.1    Hauptmann, A.G.2    Xiang, G.3
  • 9
    • 0010226736 scopus 로고    scopus 로고
    • A probabilistic analysis of the rocchio algorithm with tfidf for text categorization
    • T. Joachims. A probabilistic analysis of the rocchio algorithm with tfidf for text categorization. Technical report, DTIC Document, 1996.
    • (1996) Technical Report DTIC Document
    • Joachims, T.1
  • 10
    • 0242456822 scopus 로고    scopus 로고
    • Optimizing search engines using clickthrough data
    • T. Joachims. Optimizing search engines using clickthrough data. In SIGKDD, pages 133-142, 2002.
    • (2002) SIGKDD , pp. 133-142
    • Joachims, T.1
  • 12
    • 84876231242 scopus 로고    scopus 로고
    • Imagenet classification with deep convolutional neural networks
    • A. Krizhevsky, I. Sutskever, and G. Hinton. Imagenet classification with deep convolutional neural networks. In NIPS, pages 1106-1114, 2012.
    • (2012) NIPS , pp. 1106-1114
    • Krizhevsky, A.1    Sutskever, I.2    Hinton, G.3
  • 15
    • 0034785304 scopus 로고    scopus 로고
    • Relevance based language models
    • V. Lavrenko and W. B. Croft. Relevance based language models. In SIGIR, pages 120-127, 2001.
    • (2001) SIGIR , pp. 120-127
    • Lavrenko, V.1    Croft, W.B.2
  • 16
    • 57349180460 scopus 로고    scopus 로고
    • A cluster-based resampling method for pseudo-relevance feedback
    • K. S. Lee, W. B. Croft, and J. Allan. A cluster-based resampling method for pseudo-relevance feedback. In SIGIR, pages 235-242, 2008.
    • (2008) SIGIR , pp. 235-242
    • Lee, K.S.1    Croft, W.B.2    Allan, J.3
  • 17
    • 54049116354 scopus 로고    scopus 로고
    • Learning to video search rerank via pseudo preference feedback
    • Y. Liu, T. Mei, X.-S. Hua, J. Tang, X. Wu, and S. Li. Learning to video search rerank via pseudo preference feedback. In ICME, pages 297-300, 2008.
    • (2008) ICME , pp. 297-300
    • Liu, Y.1    Mei, T.2    Hua, X.-S.3    Tang, J.4    Wu, X.5    Li, S.6
  • 18
    • 77956019826 scopus 로고    scopus 로고
    • Positional relevance model for pseudo-relevance feedback
    • Y. Lv and C. Zhai. Positional relevance model for pseudo-relevance feedback. In SIGIR, pages 579-586, 2010.
    • (2010) SIGIR , pp. 579-586
    • Lv, Y.1    Zhai, C.2
  • 19
    • 84877618360 scopus 로고    scopus 로고
    • Fisher kernel based relevance feedback for multimodal video retrieval
    • I. Mironica, B. Ionescu, J. Uijlings, and N. Sebe. Fisher kernel based relevance feedback for multimodal video retrieval. In ICMR, pages 65-72, 2013.
    • (2013) ICMR , pp. 65-72
    • Mironica, I.1    Ionescu, B.2    Uijlings, J.3    Sebe, N.4
  • 21
    • 78149348137 scopus 로고    scopus 로고
    • Improving the fisher kernel for large-scale image classification
    • F. Perronnin, J. Sánchez, and T. Mensink. Improving the fisher kernel for large-scale image classification. In ECCV, pages 143-156, 2010.
    • (2010) ECCV , pp. 143-156
    • Perronnin, F.1    Sánchez, J.2    Mensink, T.3
  • 22
    • 84883126733 scopus 로고    scopus 로고
    • Early versus late fusion in semantic video analysis
    • C. G. Snoek, M. Worring, and A. W. Smeulders. Early versus late fusion in semantic video analysis. In Multimedia, pages 399-402, 2005.
    • (2005) Multimedia , pp. 399-402
    • Snoek, C.G.1    Worring, M.2    Smeulders, A.W.3
  • 25
    • 80052877143 scopus 로고    scopus 로고
    • Action recognition by dense trajectories
    • H. Wang, A. Klaser, C. Schmid, and C. L. Liu. Action recognition by dense trajectories. In CVPR, pages 3169-3176, 2011.
    • (2011) CVPR , pp. 3169-3176
    • Wang, H.1    Klaser, A.2    Schmid, C.3    Liu, C.L.4
  • 26
    • 77953628309 scopus 로고    scopus 로고
    • Adapting boosting for information retrieval measures
    • Q. Wu, C. J. Burges, K. M. Svore, and J. Gao. Adapting boosting for information retrieval measures. Information Retrieval, 13(3):254-270, 2010.
    • (2010) Information Retrieval , vol.13 , Issue.3 , pp. 254-270
    • Wu, Q.1    Burges, C.J.2    Svore, K.M.3    Gao, J.4
  • 27
    • 35248860273 scopus 로고    scopus 로고
    • Multimedia search with pseudo-relevance feedback
    • R. Yan, A. G. Hauptmann, and R. Jin. Multimedia search with pseudo-relevance feedback. In CVIR, pages 238-247, 2003.
    • (2003) CVIR , pp. 238-247
    • Yan, R.1    Hauptmann, A.G.2    Jin, R.3
  • 28
    • 2342504481 scopus 로고    scopus 로고
    • Negative pseudo-relevance feedback in content-based video retrieval
    • R. Yan, A. G. Hauptmann, and R. Jin. Negative pseudo-relevance feedback in content-based video retrieval. In Multimedia, pages 343-346, 2003.
    • (2003) Multimedia , pp. 343-346
    • Yan, R.1    Hauptmann, A.G.2    Jin, R.3
  • 29
    • 78650980260 scopus 로고    scopus 로고
    • Supervised reranking for web image search
    • L. Yang and A. Hanjalic. Supervised reranking for web image search. In Multimedia, pages 183-192, 2010.
    • (2010) Multimedia , pp. 183-192
    • Yang, L.1    Hanjalic, A.2
  • 30
    • 84864120582 scopus 로고    scopus 로고
    • Multimodal knowledge-based analysis in multimedia event detection
    • E. Younessian, T. Mitamura, and A. G. Hauptmann. Multimodal knowledge-based analysis in multimedia event detection. In ICMR, page 51, 2012.
    • (2012) ICMR , pp. 51
    • Younessian, E.1    Mitamura, T.2    Hauptmann, A.G.3
  • 31
    • 0034788435 scopus 로고    scopus 로고
    • A study of smoothing methods for language models applied to ad hoc information retrieval
    • C. Zhai and J. Lafferty. A study of smoothing methods for language models applied to ad hoc information retrieval. In SIGIR, pages 334-342, 2001.
    • (2001) SIGIR , pp. 334-342
    • Zhai, C.1    Lafferty, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.