Enhancing image annotation by integrating concept ontology and text-based Bayesian learning model

Proceedings of the ACM International Multimedia Conference and Exhibition

Volumn , Issue , 2007, Pages 341-344

  Shi, Rui ^a   Lee, Chin Hui ^b   Chua, Tat Seng ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Automatic image annotation; MAP; Mixture model; MLE

Indexed keywords

IMAGE RETRIEVAL; LEARNING SYSTEMS; MATHEMATICAL MODELS; ONTOLOGY; VIRTUAL REALITY;

AUTOMATIC IMAGE ANNOTATION; DATA SOURCES; MIXTURE MODELS; TRAINING SAMPLES;

BAYESIAN NETWORKS;

EID: 37849051974     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1291233.1291307     Document Type: Conference Paper

References (15)

1. K. Barnard, P. Duygulu and D. Forsyth, "Clustering Art", In Proc. Of IEEE Computer Vision and Pattern Recognition, 2001.
2. G. Carneiro and N. Vasconcelos, "Formulating Semantic Image Annotation as a Supervised Learning Problem", In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005.
3. J. P. Fan, H. Z. Luo and Y. L. Gao, "Learning the Semantics of Images by Using Unlabeled Samples", Proceedings CVPR, 2005.
4. H.M. Feng. R. Shi and T.S. Chua, "A Bootstrapping Framework for Annotating and Retrieving WWW Images", In ACMMultimedia '04, pp. 960-967, New York, 2004.
5. S.L. Feng, R. Manmatha and V. Lavrenko, "Multiple Bernoulli Relevance Models for Image and Video Annotation", Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'04.
6. S. Gao, D.-H. Wang and C.-H. Lee, "Automatic Image Annotation through Multi-Topic Text Categorization", Proc. ICASSP, Toulouse, France, May 2006.
7. th ACM SIGIR, 2003.
8. V. Lavrenko, R. Manmatha and J. Jeon, "A Model for Learning the Semantics of Pictures", NIPS, 2003.
9. G. A. Miller, R. Beckwith, C. Fellbaum, D. Gross and K. J. Miller, "Introduction to WordNet: an on-line lexical database", Intl. Jour. Of Lexicography, pp. 235-244, 1990.
10. J. Novovicova and A. Malik, "Application of Multinomial Mixture Model to Text Classification", Pattern Recognition and Image Analysis, pp. 646-653, 2003.
11. th ACM SIGIR, 2005.
12. R. Shi, T.S. Chua, C.H. Lee and S. Gao, "Bayesian Learning of Hierarchical Multinomial Mixture Models of Concepts for Automatic Image Annotation", In Proc. of CIVR '06, pp. 102-112, Arizona, United States, 2006.
13. S. Tong and E. Chang, "Support Vector Machine Active Learning for Image Retrieval", In ACM Multimedia '01, pp. 107-118, Ottawa, Canada, 2001.
14. R. Yan, and A.G. Hauptmann, "Multi-class Active Learning for Video Semantic Feature Extraction", In Proc. of ICME'04, pp. 69-72, 2004.
15. C.X. Zhai and J. Lafferty, "A Study of Smoothing Methods for Language Models Applied to Ad Hoc Information Retrieval", SIGIR '01, 2001.