메뉴 건너뛰기




Volumn , Issue , 2011, Pages 233-242

Personalizing automated image annotation using cross-entropy

Author keywords

Automated image annotation; Cross entropy optimization; Personal multimedia tagging history; Personalization

Indexed keywords

ABSOLUTE PERFORMANCE; AUTOMATIC IMAGE ANNOTATION; CONTENT-BASED; CROSS ENTROPY; GENERIC IMAGES; IMAGE ANNOTATION; PERFORMANCE MEASUREMENTS; PERSONALIZATIONS;

EID: 84455173086     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2072298.2072330     Document Type: Conference Paper
Times cited : (29)

References (29)
  • 2
    • 74049158146 scopus 로고    scopus 로고
    • NUS-WIDE: A real-world web image database from National University of Singapore
    • T.-S. Chua, J. Tang, R. Hong, H. Li, Z. Luo, and Y.-T. Zheng. NUS-WIDE: A real-world web image database from National University of Singapore. In CIVR, 2009.
    • (2009) CIVR
    • Chua, T.-S.1    Tang, J.2    Hong, R.3    Li, H.4    Luo, Z.5    Zheng, Y.-T.6
  • 3
    • 37849021285 scopus 로고    scopus 로고
    • Tagging over time: Real-world image annotation by lightweight meta-learning
    • R. Datta, D. Joshi, J. Li, and J. Wang. Tagging over time: real-world image annotation by lightweight meta-learning. In ACM Multimedia, 2007.
    • (2007) ACM Multimedia
    • Datta, R.1    Joshi, D.2    Li, J.3    Wang, J.4
  • 4
    • 74049123062 scopus 로고    scopus 로고
    • Style modeling for tagging personal photo collections
    • M. Duan, A. Ulges, T. Breuel, and X.-Q. Wu. Style modeling for tagging personal photo collections. In CIVR, 2009.
    • (2009) CIVR
    • Duan, M.1    Ulges, A.2    Breuel, T.3    Wu, X.-Q.4
  • 6
    • 77953202699 scopus 로고    scopus 로고
    • TagProp: Discriminative metric learning in nearest neighbor models for image auto-annotation
    • M. Guillaumin, T. Mensink, J. Verbeek, and C. Schmid. TagProp: Discriminative metric learning in nearest neighbor models for image auto-annotation. In ICCV, 2009.
    • (2009) ICCV
    • Guillaumin, M.1    Mensink, T.2    Verbeek, J.3    Schmid, C.4
  • 7
    • 54549085366 scopus 로고    scopus 로고
    • Description of interest regions with local binary patterns
    • M. Heikkilä, M. Pietikäinen, and C. Schmid. Description of interest regions with local binary patterns. Pattern Recogn., 42:425-436, 2009.
    • (2009) Pattern Recogn. , vol.42 , pp. 425-436
    • Heikkilä, M.1    Pietikäinen, M.2    Schmid, C.3
  • 9
    • 43249117136 scopus 로고    scopus 로고
    • Real-time computerized annotation of pictures
    • J. Li and J. Wang. Real-time computerized annotation of pictures. IEEE Trans. Pattern Anal. Mach. Intell., 30(6):985-1002, 2008.
    • (2008) IEEE Trans. Pattern Anal. Mach. Intell. , vol.30 , Issue.6 , pp. 985-1002
    • Li, J.1    Wang, J.2
  • 10
    • 70350333307 scopus 로고    scopus 로고
    • Learning social tag relevance by neighbor voting
    • X. Li, C. Snoek, and M. Worring. Learning social tag relevance by neighbor voting. IEEE Trans. Multimedia, 11(7):1310-1322, 2009.
    • (2009) IEEE Trans. Multimedia , vol.11 , Issue.7 , pp. 1310-1322
    • Li, X.1    Snoek, C.2    Worring, M.3
  • 11
    • 77955879220 scopus 로고    scopus 로고
    • Unsupervised multi-feature tag relevance learning for social image retrieval
    • X. Li, C. Snoek, and M. Worring. Unsupervised multi-feature tag relevance learning for social image retrieval. In CIVR, 2010.
    • (2010) CIVR
    • Li, X.1    Snoek, C.2    Worring, M.3
  • 14
    • 79953043001 scopus 로고    scopus 로고
    • Textual query of personal photos facilitated by large-scale web data
    • Y. Liu, D. Xu, I. Tsang, and J. Luo. Textual query of personal photos facilitated by large-scale web data. IEEE Trans. Pattern Anal. Mach. Intell., 33(5):1022-1036, 2011.
    • (2011) IEEE Trans. Pattern Anal. Mach. Intell. , vol.33 , Issue.5 , pp. 1022-1036
    • Liu, Y.1    Xu, D.2    Tsang, I.3    Luo, J.4
  • 15
    • 70350656056 scopus 로고    scopus 로고
    • Event recognition: Viewing the world with a third eye
    • J. Luo, J. Yu, D. Joshi, and W. Hao. Event recognition: viewing the world with a third eye. In ACM Multimedia, 2008.
    • (2008) ACM Multimedia
    • Luo, J.1    Yu, J.2    Joshi, D.3    Hao, W.4
  • 17
    • 84976702763 scopus 로고
    • WordNet: A lexical database for english
    • G. Miller. WordNet: a lexical database for english. Commun. ACM, 38(11):39-41, 1995.
    • (1995) Commun. ACM , vol.38 , Issue.11 , pp. 39-41
    • Miller, G.1
  • 18
    • 0035328421 scopus 로고    scopus 로고
    • Modeling the shape of the scene: A holistic representation of the spatial envelope
    • A. Oliva and A. Torralba. Modeling the shape of the scene: a holistic representation of the spatial envelope. Int. J. Comput. Vision, 42(3):145-175, 2001.
    • (2001) Int. J. Comput. Vision , vol.42 , Issue.3 , pp. 145-175
    • Oliva, A.1    Torralba, A.2
  • 20
    • 78651408054 scopus 로고    scopus 로고
    • Semantic analysis and retrieval in personal and social photo collections
    • P. Sandhaus and S. Boll. Semantic analysis and retrieval in personal and social photo collections. Multimedia Tools Appl., 51(1):5-33, 2011.
    • (2011) Multimedia Tools Appl. , vol.51 , Issue.1 , pp. 5-33
    • Sandhaus, P.1    Boll, S.2
  • 21
    • 84455207334 scopus 로고    scopus 로고
    • Quest for relevant tags using local interaction networks and visual content
    • N. Sawant, R. Datta, J. Li, and J. Wang. Quest for relevant tags using local interaction networks and visual content. In ACM MIR, 2010.
    • (2010) ACM MIR
    • Sawant, N.1    Datta, R.2    Li, J.3    Wang, J.4
  • 22
    • 78650974747 scopus 로고    scopus 로고
    • Leveraging loosely-tagged images and inter-object correlations for tag recommendation
    • Y. Shen and J. Fan. Leveraging loosely-tagged images and inter-object correlations for tag recommendation. In ACM Multimedia, 2010.
    • (2010) ACM Multimedia
    • Shen, Y.1    Fan, J.2
  • 23
    • 57549106456 scopus 로고    scopus 로고
    • Classification and annotation of digital photos using optical context data
    • P. Sinha and R. Jain. Classification and annotation of digital photos using optical context data. In CIVR, 2008.
    • (2008) CIVR
    • Sinha, P.1    Jain, R.2
  • 25
    • 79952402835 scopus 로고    scopus 로고
    • Image annotation by knn-sparse graph-based label propagation over noisily tagged web images
    • J. Tang, R. Hong, S. Yan, T.-S. Chua, G.-J. Qi, and R. Jain. Image annotation by knn-sparse graph-based label propagation over noisily tagged web images. ACM Trans. Intell. Syst. Technol., 2:14:1-14:15, 2011.
    • (2011) ACM Trans. Intell. Syst. Technol. , vol.2 , pp. 141-1415
    • Tang, J.1    Hong, R.2    Yan, S.3    Chua, T.-S.4    Qi, G.-J.5    Jain, R.6
  • 26
    • 77955654853 scopus 로고    scopus 로고
    • Large scale image annotation: Learning to rank with joint word-image embeddings
    • J. Weston, S. Bengio, and N. Usunier. Large scale image annotation: learning to rank with joint word-image embeddings. Mach. Learn., 81:21-35, 2010.
    • (2010) Mach. Learn. , vol.81 , pp. 21-35
    • Weston, J.1    Bengio, S.2    Usunier, N.3
  • 27
    • 72449130482 scopus 로고    scopus 로고
    • Distance metric learning from uncertain side information with application to automated photo tagging
    • L. Wu, S. Hoi, R. Jin, J. Zhu, and N. Yu. Distance metric learning from uncertain side information with application to automated photo tagging. In ACM Multimedia, 2009.
    • (2009) ACM Multimedia
    • Wu, L.1    Hoi, S.2    Jin, R.3    Zhu, J.4    Yu, N.5
  • 28
    • 0036448175 scopus 로고    scopus 로고
    • Color texture moment for content-based image retrieval
    • H. Yu, M. Li, H.-J. Zhang, and J. Feng. Color texture moment for content-based image retrieval. In ICIP, 2002.
    • (2002) ICIP
    • Yu, H.1    Li, M.2    Zhang, H.-J.3    Feng, J.4
  • 29
    • 78650977486 scopus 로고    scopus 로고
    • Image tag refinement towards low-rank, content-tag prior and error sparsity
    • G. Zhu, S. Yan, and Y. Ma. Image tag refinement towards low-rank, content-tag prior and error sparsity. In ACM Multimedia, 2010.
    • (2010) ACM Multimedia
    • Zhu, G.1    Yan, S.2    Ma, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.