Mining high-level features from video using associations and correlations

ICSC 2009 - 2009 IEEE International Conference on Semantic Computing

Volumn , Issue , 2009, Pages 137-144

  Lin, Lin ^a   Shyu, Mei Ling ^a  

^a University of Miami College of Engineering   (United States)

Author keywords

Association rule mining; Concept detection; Multiple Correspondence Analysis (MCA)

Indexed keywords

ASSOCIATION CLASSIFICATION; ASSOCIATION RULE MINING; AUTOMATIC DISCOVERY; BENCHMARK DATA; COMBINED MEASURE; CONCEPT CLASS; CONCEPT DETECTION; CONTENT-BASED MULTIMEDIA RETRIEVAL; HARMONIC MEAN; HIGH EFFICIENCY; HIGH-LEVEL FEATURES; MULTIPLE CORRESPONDENCE ANALYSIS; PERFORMANCE COMPARISON; RULE GENERATION; RULE SELECTION; SEMANTIC CONCEPT DETECTION; TRECVID;

ASSOCIATION RULES; CONTENT BASED RETRIEVAL; DECISION TREES; MAGNETIC LOGIC DEVICES; NEURAL NETWORKS; SEMANTICS;

ASSOCIATIVE PROCESSING;

EID: 73449130148     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICSC.2009.59     Document Type: Conference Paper

References (19)

1. A. Kouomou-Choupo, L. Berti-Equille, and A. Morin, "Multimedia indexing and retrieval with features association rules mining [image databases]," in IEEE International Conference on Multimedia and Expo (ICME04), June 2004, pp. 1299-1302.
2. V. S. Tseng, M.-H. Wang, and J.-H. Su, "A new method for image classification by using multilevel association rules," in IEEE International Conference on Data Engineering (ICDE05), April 2005, pp. 1180-1188.
3. H. H. Malik and J. R. Kender, "Clustering web images using association rules, interestingness measures, and hypergraph partitions," in ACM International Conference on Web Engineering (ICWE06), July 2006, pp. 48-55.
4. R. Agrawal and R. Srikant, "Fast algorithms for mining association rules in large databases," in International Conference on Very Large Data Bases (VLDB94), September 1994, pp. 487-499.
5. X. Zhu, X. Wu, A. K. Elmagarmid, Z. Feng, and L. Wu, "Video data mining: Semantic indexing and event detection from the association perspective," IEEE Transactions on Knowledge and Data Engineering, vol. 17, no. 5, pp. 665-677, May 2005.
6. M. H. Kolekar and S. Sengupta, "Semantic concept extraction from sports video for highlight generation," in ACM International Conference on Mobile Multimedia Communications (MobiMedia06), September 2006, pp. 1-6.
7. M. Chen, S.-C. Chen, and M.-L. Shyu, "Hierarchical temporal association mining for video event detection in video databases," in IEEE International Workshop on Multimedia Databases and Data Management (MDDM07), April 2007, pp. 137-145.
8. N. Zhao, S.-C. Chen, and S. H. Rubin, "Automated multimedia systems training using association rule mining," in IEEE International Conference on Information Reuse and Integration (IRI07), August 2007, pp. 373-378.
9. F. Anwar and A. Naftel, "Video event modelling and association rule mining in multimedia surveillance systems," in International Conference on Visual Information Engineering (VIE08), August 2008, pp. 426-431.
10. L. Lin, G. Ravitz, M.-L. Shyu, and S.-C. Chen, "Video semantic concept discovery using multimodal-based association classification," in IEEE International Conference on Multimedia and Expo (ICME07), July 2007, pp. 859-862.
11. -, "Correlation-based video semantic concept detection using multiple correspondence analysis," in IEEE International Symposium on Multimedia (ISM08), December 2008, pp. 316-321.
12. L. Lin, M.-L. Shyu, G. Ravitz, and S.-C. Chen, "Video semantic concept detection via associative classification," in IEEE International Conference on Multimedia and Expo (ICME09), July 2009, pp. 418-421.
13. K.-H. Liu, M.-F. Weng, C.-Y. Tseng, Y.-Y. Chuang, and M.-S. Chen, "Association and temporal rule mining for post-filtering of semantic concept detection in video," IEEE Transactions on Multimedia, vol. 10, pp. 240-251, February 2008.
14. Q. Song, M. Shepperd, M. Cartwright, and C. Mair, "Software defect association mining and defect correction effort prediction," IEEE Transactions on Software Engineering, vol. 32, pp. 69-82, February 2006.
15. G. Yang, K. Shimada, S. Mabu, and K. Hirasawa, "A personalized association rule ranking method based on semantic similarity and evolutionary computation," in IEEE Congress on Evolutionary Computation (CEC08), June 2008, pp. 487-494.
16. A. F. Smeaton, P. Over, and W. Kraaij, "Evaluation campaigns and TRECVid," in ACM International Workshop on Multimedia Information Retrieval (MIR06), October 2006, pp. 321-330.
17. I. H. Witten and E. Frank, Data Mining: Practical Machine Learning Tools and Techniques, 2nd ed. Morgan Kaufmann, June 2005.
18. U. M. Fayyad and K. B. Irani, "On the handling of continuous-valued attributes in decision tree generation," Machine Learning, vol. 8, pp. 87-102, January 1992.
19. N. J. Salkind, Ed., Encyclopedia of Measurement and Statistics. SAGE Publications, Inc, 2007.