Abstract
A common approach to the problem of SED in collections of multimedia relies on the use of clustering methods. Due to the heterogeneity of features associated with multimedia items in such collections, such a clustering task is very challenging and special multimodal clustering approaches need to be deployed. In this paper, we present a scalable graph-based multimodal clustering approach for SED in large collections of multimedia. The proposed approach utilizes example relevant clusterings to learn a model of the “same event” relationship between two items in the multimodal domain and subsequently to organize the items in a graph. Two variants of the approach are presented: the first based on a batch and the second on an incremental community detection algorithm. Experimental results indicate that both variants provide excellent clustering performance.
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References
Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-Up Robust Features (SURF). Comp. Vis. Image Underst. 110(3), 346–359 (2008)
Becker, H., Naaman, M., Gravano, L.: Learning similarity metrics for event identification in social media. In: Proceedings of the Third ACM International Conference on Web Search and Data Mining, WSDM 2010, pp. 291–300. ACM, New York (2010)
Bekkerman, R., Jeon, J.: Multi-modal clustering for multimedia collections. In: CVPR (2007)
Brenner, M., Izquierdo, E.: Mediaeval benchmark: Social Event Detection in collaborative photo collections. In: MediaEval. CEUR Workshop Proceedings (2011)
Cai, X., Nie, F., Huang, H., Kamangar, F.: Heterogeneous image feature integration via multi-modal spectral clustering. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR, pp. 1977–1984 (June 2011)
Fortunato, S.: Community detection in graphs. Physics Reports 486(3-5), 75–174 (2010)
Goder, A., Filkov, V.: Consensus clustering algorithms: Comparison and refinement. In: Ian Munro, J. (ed.) Proceedings of the Workshop on Algorithm Engineering and Experiments, ALENEX 2008, San Francisco, California, USA, pp. 109–117. SIAM (January 19, 2008)
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The weka data mining software: an update. SIGKDD Explorations Newsletter 11(1), 10–18 (2009)
Jegou, H., Douze, M., Schmid, C.: Product quantization for nearest neighbor search. IEEE Transactions on Pattern Analysis and Machine Intelligence 33(1), 117–128 (2011)
Jégou, H., Douze, M., Schmid, C., Pérez, P.: Aggregating local descriptors into a compact image representation. In: 23rd IEEE Conference on Computer Vision & Pattern Recognition, CVPR 2010, pp. 3304–3311. IEEE Computer Society, San Francisco (2010)
Khalidov, V., Forbes, F., Horaud, R.P.: Conjugate mixture models for clustering multimodal data. Neural Computation 23(2), 517–557 (2011)
Li, Y., Crandall, D.J., Huttenlocher, D.P.: Landmark classification in large-scale image collections. In: IEEE 12th International Conference on Computer Vision, ICCV 2009, Kyoto, Japan, September 27 - October 4, pp. 1957–1964. IEEE (2009)
Liu, X., Troncy, R., Huet, B.: Using social media to identify events. In: ACM Multimedia 3rd Workshop on Social Media, WSM 2011, Scottsdale, Arizona, USA, November 18-December 1, p. 11 (2011)
Manning, C.D., Raghavan, P., Schütze, H.: Introduction to Information Retrieval. Cambridge University Press, New York (2008)
Nguyen, N.P., Dinh, T.N., Xuan, Y., Thai, M.T.: Adaptive algorithms for detecting community structure in dynamic social networks. In: 30th IEEE International Conference on Computer Communications, Joint Conference of the IEEE Computer and Communications Societies, INFOCOM 2011, Shanghai, China, April 10-15, pp. 2282–2290. IEEE (2011)
Oliva, A., Torralba, A.: Modeling the shape of the scene: A holistic representation of the spatial envelope. Int. J. Comput. Vision 42(3), 145–175 (2001)
Papadopoulos, S., Kompatsiaris, Y., Vakali, A., Spyridonos, P.: Community detection in social media. Data Mining and Knowledge Discovery 24(3), 515–554 (2012)
Papadopoulos, S., Schinas, E., Mezaris, V., Troncy, R., Kompatsiaris, I.: The 2012 Social Event Detection dataset. In: 4th ACM Multimedia Systems, Dataset Session, MMSys 2013, Oslo, Norway, February 27-March 1 (2013)
Papadopoulos, S., Schinas, E., Mezaris, V., Troncy, R., Kompatsiaris, Y.: Social Event Detection at MediaEval 2012: Challenges, Dataset and Evaluation. In: MediaEval 2012 Workshop, Pisa, Italy, October 4-5 (2012)
Papadopoulos, S., Troncy, R., Mezaris, V., Huet, B., Kompatsiaris, I.: Social Event Detection at Mediaeval 2011: Challenges, dataset and evaluation. In: MediaEval. CEUR Workshop Proceedings (2011)
Papadopoulos, S., Zigkolis, C., Kompatsiaris, Y., Vakali, A.: CERTH@Mediaeval 2011 social event detection task. In: MediaEval. CEUR Workshop Proceedings (2011)
Papadopoulos, S., Zigkolis, C., Kompatsiaris, Y., Vakali, A.: Cluster-based landmark and event detection for tagged photo collections. IEEE Multimedia 18(1), 52–63 (2011)
Petkos, G., Papadopoulos, S., Kompatsiaris, Y.: Social event detection using multimodal clustering and integrating supervisory signals. In: Proceedings of the 2nd ACM International Conference on Multimedia Retrieval, ICMR 2012, pp. 23:1–23:8. ACM, New York (2012)
Phuvipadawat, S., Murata, T.: Breaking news detection and tracking in twitter. In: IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, vol. 3, pp. 120–123 (2010)
Rendle, S., Schmidt-Thieme, L.: Scaling record linkage to non-uniform distributed class sizes. In: Washio, T., Suzuki, E., Ting, K.M., Inokuchi, A. (eds.) PAKDD 2008. LNCS (LNAI), vol. 5012, pp. 308–319. Springer, Heidelberg (2008)
Reuter, T., Cimiano, P.: Event-based classification of social media streams. In: Proceedings of the 2nd ACM International Conference on Multimedia Retrieval, ICMR 2012, pp. 22:1–22:8. ACM, New York (2012)
Schinas, E., Mantziou, E., Papadopoulos, S., Petkos, G., Kompatsiaris, Y.: CERTH @ Mediaeval 2013 Social Event Detection Task. In: MediaEval. CEUR Workshop Proceedings (2013)
Schinas, E., Petkos, G., Papadopoulos, S., Kompatsiaris, Y.: CERTH @ Mediaeval 2012 Social Event Detection Task. In: MediaEval. CEUR Workshop Proceedings, vol. 927 (2012)
Snoek, C.G.M., Worring, M., Smeulders, A.W.M.: Early versus late fusion in semantic video analysis. In: Proceedings of the 13th Annual ACM International Conference on Multimedia, MULTIMEDIA 2005, pp. 399–402. ACM, New York (2005)
Xu, X., Yuruk, N., Feng, Z., Schweiger, T.A.J.: Scan: a structural clustering algorithm for networks. In: Proceedings of the 13th ACM SIGKDD, KDD 2007, pp. 824–833. ACM, NY (2007)
Ye, Z., Hu, S., Yu, J.: Adaptive clustering algorithm for community detection in complex networks. Physical Review E 78(4) (2008)
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Petkos, G., Papadopoulos, S., Schinas, E., Kompatsiaris, Y. (2014). Graph-Based Multimodal Clustering for Social Event Detection in Large Collections of Images. In: Gurrin, C., Hopfgartner, F., Hurst, W., Johansen, H., Lee, H., O’Connor, N. (eds) MultiMedia Modeling. MMM 2014. Lecture Notes in Computer Science, vol 8325. Springer, Cham. https://doi.org/10.1007/978-3-319-04114-8_13
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DOI: https://doi.org/10.1007/978-3-319-04114-8_13
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