Automatic evaluation method for rushes summarization: Experimentation and analysis

2008 International Workshop on Content-Based Multimedia Indexing, CBMI 2008, Conference Proceedings

Volumn , Issue , 2008, Pages 518-525

  Dumont, Emilie ^a   Mérialdo, Bernard ^a  

^a EURECOM   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; IMAGE SEGMENTATION; INDEXING (OF INFORMATION); LEARNING ALGORITHMS; VIDEO RECORDING;

AUTOMATIC EVALUATION; AUTOMATIC SYSTEMS; CONTENT-BASED MULTIMEDIA; EVALUATION METHODOLOGIES; GROUND TRUTH; MACHINE-LEARNING TECHNIQUES; RIGOROUS EVALUATION; TRECVID; VIDEO SUMMARIES; VIDEO SUMMARIZATION SYSTEMS;

LEARNING SYSTEMS;

EID: 51849132702     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CBMI.2008.4564991     Document Type: Conference Paper

References (26)

1. H. Jing, R. Barzilay, K. McKeown, and M. Elhadad, "Summarization evaluation methods experiments and analysis," .
2. Cuneyt M. Taskiran, "Evaluation of automatic video summarization systems," 2006, SPIE.
3. M.G. Christel, "Evaluation and user studies with respect to video summarization and browsing," .
4. Paul Over, Alan F. Smeaton, and Philip Kelly, "The TRECVID 2007 BBC rushes summarization evaluation pilot," in Proceedings of the TRECVID Workshop on Video Summarization (TVS'07), New York, NY, September 2007, pp. 1-15, ACM Press.
5. A.M. Ferman, A.M.; Tekalp, "Two-stage hierarchical video summary extraction to match low-level user browsing preferences," Multimedia, IEEE Transactions on, vol. 5, no. 2, pp. 244-256, June 2003.
6. A.M.; Mehrotra R. Ekin, A.; Tekalp, "Automatic soccer video analysis and summarization," Image Processing, IEEE Transactions on, vol. 12, no. 7, pp. 796-807, July 2003.
7. Ba Tu Truong and Svetha Venkatesh, "Video abstraction: A systematic review and classification," ACM Trans. Multimedia Comput. Commun. Appl., vol. 3, no. 1, 2007.
8. Emilie Dumont and Bernard Mérialdo, "Split-screen dynamically accelerated video summaries," in MM 2007, 15th international ACM conference on multimedia, September 24-29, 2007, Augsburg, Germany, Sep 2007.
9. Alexander G. Hauptmann, Michael G. Christel, Wei-Hao Lin, Bryan Maher, Jun Yang, Robert V. Baron, and Guang Xiang, "Clever clustering vs. simple speed-up for summarizing rushes," in TVS '07: Proceedings of the international workshop on TRECVID video summarization, New York, NY, USA, 2007, pp. 20-24, ACM.
10. http://www.cs.waikato.ac.nz/ml/weka/, ," .
11. Y. Freund and L. Mason, "The alternating decision tree learning algorithm," in Proceeding of the Sixteenth International Conference on Machine Learning, Bled, Slovenia, 1999, pp. 124-133.
12. Ron Kohavi, "The power of decision tables," in 8th European Conference on Machine Learning. 1995, pp. 174-189, Springer.
13. D. Aha and D. Kibler, "Instance-based learning algorithms," Machine Learning, vol. 6, pp. 37-66, 1991.
14. Ross Quinlan, C4.5: Programs for Machine Learning, Morgan Kaufmann Publishers, San Mateo, CA, 1993.
15. William W. Cohen, "Fast effective rule induction," in Twelfth International Conference on Machine Learning. 1995, pp. 115-123, Morgan Kaufmann.
16. John G. Cleary and Leonard E. Trigg, "K*: An instance-based learner using an entropic distance measure," in 12th International Conference on Machine Learning, 1995, pp. 108-114.
17. Zijian Zheng and G. Webb, "Lazy learning of bayesian rules," Machine Learning, vol. 4, no. 1, pp. 53-84, 2000.
18. S. le Cessie and J.C. van Houwelingen, "Ridge estimators in logistic regression," Applied Statistics, vol. 41, no. 1, pp. 191-201, 1992.
19. George H. John and Pat Langley, "Estimating continuous distributions in bayesian classifiers," in Eleventh Conference on Uncertainty in Artificial Intelligence, San Mateo, 1995, pp. 338-345, Morgan Kaufmann.
20. Richard Duda and Peter Hart, Pattern Classification and Scene Analysis, Wiley, New York, 1973.
21. Ron Kohavi, "Scaling up the accuracy of naive-bayes classifiers: A decision-tree hybrid," in Second International Conference on Knoledge Discovery and Data Mining, 1996, pp. 202-207.
22. Sylvain Roy, "Nearest neighbor with generalization," 2002.
23. R.C. Holte, "Very simple classification rules perform well on most commonly used datasets," Machine Learning, vol. 11, pp. 63-91, 1993.
24. Eibe Frank and Ian H. Witten, "Generating accurate rule sets without global optimization," in Fifteenth International Conference on Machine Learning, J. Shavlik, Ed. 1998, pp. 144-151, Morgan Kaufmann.
25. Leo Breiman, "Random forests," Machine Learning, vol. 45, no. 1, pp. 5-32, 2001.
26. Brian R. Gaines and Paul Compton, "Induction of ripple-down rules applied to modeling large databases," J. Intell. Inf. Syst., vol. 5, no. 3, pp. 211-228, 1995.