Semi-automatic semantic annotation of images using machine learning techniques

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2870, Issue , 2003, Pages 550-565

  Marques, Oge ^a   Barman, Nitish ^a  

^a Florida Atlantic Univ   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COST EFFECTIVENESS; IMAGE RETRIEVAL; LEARNING ALGORITHMS; LEARNING SYSTEMS; SOCIAL NETWORKING (ONLINE); WEBSITES;

BOTTOM LAYERS; MACHINE LEARNING TECHNIQUES; SEMANTIC ANNOTATIONS; SEMANTIC MARKUP; SEMI-AUTOMATICS; THREELAYER ARCHITECTURE; VISUAL INFORMATION; VISUAL LEVELS;

SEMANTIC WEB;

EID: 0242339626     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-39718-2_35     Document Type: Article

References (24)

1. Adobe XMP. http://www.adobe.com/products/xmp/main.html.
2. S. Aksoy and R.M. Haralick. Graph-theoretic clustering for image grouping and retrieval. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages 23-25, Fort Collins, CO, USA, 1999.
3. ARTISTE (An integrated Art Analysis and Navigation Environment). http://www.ecs.soton.ac.uk/∼km/projs/artiste/.
4. E. Chang, K. Goh, G. Sychay, and G. Wu. CBSA: content-based soft annotation for multimodal image retrieval using bayes point machines. IEEE Transactions on Circuits and Systems for Video Technology, 13(1):26-38, January 2003.
5. I. J. Cox, M. L. Miller, T. Papathomas, J. Ghosn, and P.N. Yianilos. Hidden annotation in content based image retrieval. In Proceedings of the IEEE Workshop on Content-Based Access of Image and Video Libraries, pages 76-81, San Juan, Puerto Rico, 1997.
6. M. Erdmann, A. Maedche, H. Schnurr, and S. Staab. From manual to semi-automatic semantic annotation: About ontology-based text annotation tools. In Proceedings of the COLING 2000 Workshop on Semantic Annotation and Intelligent Content, Luxembourg, 2000.
7. Y. Gong, G. Proietti, and C. Faloutsos. Image indexing and retrieval based on human perceptual color clustering. In Proceedings in IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages 578-583, 1998.
8. Google™ image search. http://www.google.com/imghp.
9. S. Handschuh, S. Staab, and F. Ciravegna. S-CREAM - Semi-automatic CREAtion of Metadata. In Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management (EKAW02), October 2002.
10. S. Handschuh, S. Staab, and A. Maedche. CREAM - creating relational metadata with a component-based, ontology-driven annotation framework. In Proceedings of the International Semantic Web Working Symposium, Stanford University, California, USA, 2001.
11. J. Hendler. Agents and the semantic web. IEEE Intelligent Systems, March/April 2001.
12. J. Hunter. Adding Multimedia to the Semantic Web - Building an MPEG-7 Ontology. In Proceedings of the International Semantic Web Working Symposium, Stanford University, California, USA, 2001.
13. ImageRover. http://www.cs.bu.edu/faculty/sclaroff/ivc/ImageRover/Home.html.
14. S. Krishnamachari and M. Abdel-Mottaleb. Image browsing using hierarchical clustering. In Proceedings of the IEEE International Symposium on Computers and Communications, pages 301-307, 1999.
15. Y. Lafon and B. Bos. Describing and retrieving photos using rdf and http. Technical report, W3C, April 2002. http://www.w3.org/TR/photo-rdf.
16. O. Marques and B. Furht. Content-Based Image and Video Retrieval. Kluwer Academic Publishers, Norwell, MA, 2002.
17. O. Marques and B. Furht. MUSE: A content-based image search and retrieval system using relevance feedback. Multimedia Tools and Applications, May 2002.
18. R.E. Neapolitan. Learning Bayesian Networks. Prentice-Hall, Upper Saddle River, NJ, 2004.
19. NISO Z39.87-2002 AIIM 20-2002 data dictionary - technical metadata for digital still images. http://www.niso.org/committees/index.html.
20. Y. Rui, T. S. Huang, and S.-F. Chang. Image retrieval: Current techniques, promising directions and open issues. Journal of Visual Communication and Image Representation, 10(1):1-23, March 1999.
21. S. Sclaroff, M. La Cascia, and S. Sethi. Unifying textual and visual cues for content-based image retrieval on the world wide web. Computer Vision and Image Understanding, 75(1/2):86-98, July/August 1999.
22. SCULPTEUR (Semantic and Content-based mULtimedia exPloiTation for EURopean benefit). http://ww.sculpteurweb.org/.
23. th ACM International Multimedia Conference, pages 3-12, Bristol, England, 1998.
24. A.W.M. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain. Content-based image retrieval at the end of the early years. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(12):1349-1380, December 2000.