Issue No.02 - April-June (2009 vol.16)
pp: 26-41
Apostol Natsev , IBM T.J. Watson Research Center
Rong Yan , IBM T.J. Watson Research Center
<p>This article proposes formal models for two commonly used methods—tagging and browsing—and investigates new approaches to improve the efficiency of manual image annotation.</p>
tagging, browsing, manual image annotation, hybrid image annotation, learning-based annotation, graphics and multimedia
Apostol Natsev, Rong Yan, "Hybrid Tagging and Browsing Approaches for Efficient Manual Image Annotation", IEEE MultiMedia, vol.16, no. 2, pp. 26-41, April-June 2009, doi:10.1109/MMUL.2009.28
1. J. Kustanowitz and B. Shneiderman, Motivating Annotation for Personal Digital Photo Libraries: Lowering Barriers while Raising Incentives, tech. report, HCIL, Univ. of Maryland, 2004.
2. K. Barnard et al., "Matching Words and Pictures," J. Machine Learning Research, vol. 3, 2003, pp. 1107-1135.
3. J. Jeon, V. Lavrenko, and R. Manmatha, "Automatic Image Annotation and Retrieval Using Cross-Media Relevance Models," Proc. 26th Ann. Int'l ACM SIGIR Conf. Research and Development in Information Retrieval, ACM Press, 2003, pp. 119-126.
4. J. Li and J.Z. Wang, "Real-Time Computerized Annotation of Pictures," Proc. ACM Int'l Conf. Multimedia, ACM Press, 2006, pp. 911-920.
5. J. Li and J.Z. Wang, Real-Time Computerized Annotation of Pictures, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 30, no. 6, 2008, pp. 985-1002.
6. P. Over et al., "Trecvid 2006 Overview," Proc. NIST Trecvid-2006, NIST, 2006.
7. C. Halaschek-Wiener et al., Photostuff—An Image Annotation Tool for the Semantic Web, Proc. 4th Int'l Semantic Web Conf., 2005.
8. L. von Ahn and L. Dabbish, "Labeling Images with a Computer Game," Proc. SIGCHI Conf. Human Factors in Computing Systems, ACM Press, 2004, pp. 319-326.
9. G.W. Furnas et al., "The Vocabulary Problem in Human–System Communication," Comm. ACM, vol. 30, no. 11, 1987, pp. 964-971.
10. A. Wilhelm et al., "Photo Annotation on a Camera Phone," CHI Extended Abstracts on Human Factors in Computing Systems, ACM Press, 2004, pp. 1403-1406.
11. T. Volkmer, J.R. Smith, and A. Natsev, "A Web-Based System for Collaborative Annotation of Large Image and Video Collections: An Evaluation and User Study," Proc. 13th ACM Int'l Conf. Multimedia, ACM Press, 2005, pp. 892-901.
12. A.G. Hauptmann et al., "Extreme Video Retrieval: Joint Maximization of Human and Computer Performance," Proc. 14th Ann. ACM Int'l Conf. Multimedia, ACM Press, 2006, pp. 385-394.
13. J. Zhu and T. Hastie, "Support Vector Machines, Kernel Logistic Regression and Boosting," Proc. 3rd Int'l Workshop Multiple Classifier Systems, Springer-Verlag, 2002, pp. 16-26.
14. G. Kimeldorf and G. Wahba, "Some Results on Tchebycheffian Spline Functions," J. Mathematical Analysis and Applications, vol. 33, 1971, pp. 82-95.
15. M. Naphade et al., "Large-Scale Concept Ontology for Multimedia," IEEE MultiMedia, vol. 13, no. 3, 2006, pp. 86-91.
16. Y. Yang and J.O. Pedersen, "A Comparative Study on Feature Selection in Text Categorization," Proc. 14th Intl. Conf. Machine Learning, Morgan Kaufmann Publishers, 1997, pp. 412-420.
17. H. Wactlar et al., "Lessons Learned from the Creation and Deployment of a Terabyte Digital Video Library," Computer, vol. 32, no. 2, 1999, pp. 66-73.
18. A.F. Smeaton, P. Over, and W. Kraaij, "Evaluation Campaigns and Trecvid," Proc 8th ACM Int'l Workshop Multimedia Information Retrieval, ACM Press, 2006, pp. 321-330.
19. M. Campbell et al., "IBM Research Trecvid-2007 Video Retrieval System," Proc. NIST Trecvid-2007, NIST, 2007.
20. R. Yan and A.G. Hauptmann, "A Review of Text and Image Retrieval Approaches for Broadcast News Video," Information Retrieval, vol. 10, nos. 4-5, 2007, pp. 445-484.