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An enhanced content selection mechanism for personalization of video news programmes

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Abstract

In this paper, we propose a content selection framework that improves the users’ experience when they are enriching or authoring pieces of news. This framework combines a variety of techniques to retrieve semantically related videos, based on a set of criteria which are specified automatically depending on the media’s constraints. The combination of different content selection mechanisms can improve the quality of the retrieved scenes, because each technique’s limitations are minimized by other techniques’ strengths. We present an evaluation based on a number of experiments, which show that the retrieved results are better when all criteria are used at time.

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Similar content being viewed by others

Notes

  1. http://www.youtube.com.

  2. http://www.facebook.com.

  3. http://www.flickr.com.

  4. http://www.orkut.com.

  5. http://www.del.icio.us.com.

  6. Polysemy occurs when a word has multiple meanings. Synonymy occurs when two or more words have the same or nearly the same meaning.

  7. http://ccextractor.sourceforge.net.

  8. http://msdn.microsoft.com/en-us/library/dd390950(VS.85).aspx.

  9. http://www.virtualdub.org.

  10. http://www.irfanview.com.

  11. http://faint.sourceforge.net.

  12. http://www.chiariglione.org/mpeg/standards/mpeg-7/mpeg-7.htm.

  13. http://www.tv-anytime.org.

  14. The term ‘document’ will be used in the context of this paper to represent a unique scene, i.e., a piece of news.

  15. http://trecvid.nist.gov/.

  16. http://www.science.uva.nl/research/mediamill/.

  17. This is the case of main anchors, who are shown in almost all scenes.

  18. The process of reading and assigning the person’s name to the detected face is executed manually in this paper; however, Optical Character Recognition (OCR) [32] could be used, as described in many papers available on the literature.

References

  1. Abowd, G.D., Mynatt, E.D.: Charting past, present, and future research in ubiquitous computing. ACM. Trans. Comput. Hum. Interact. 7(1), 29–58 (2000)

    Article  Google Scholar 

  2. Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE. Trans. Knowl. Data Eng. 17(6), 734–749 (2005)

    Article  Google Scholar 

  3. Angeletou, S., Sabou, M., Motta, E.: Folksonomy enrichment and search. In: Aroyo, L., Traverso, P., Ciravegna, F., Cimiano, P., Heath, T., Hyvonen, E., Mi-zoguchi, R., Oren, E., Sabou, M., Simperl, E.P.B. (eds.) 6th. European Semantic Web Conference, volume 5554 of Lecture Notes in Computer Science, pp. 801–805, Springer (2009)

  4. Antonellis, I., Bouras, C., Poulopoulos, V.: Personalized news categorization through scalable text classification. In: Zhou, X., Li, J., Shen, H.T., Kitsuregawa, M., Zhang, Y. (eds.) 8th Asia-Pacific Web Conference, volume 3841 of Lecture Notes in Computer Science, pp. 391–401. Springer (2006)

  5. Boll, S., Sandhaus, P., Westermann, U.: Semantics, content, and structure of many for the creation of peronal photo albums. In: Proceedings of MM’07, pp. 641–650 (2007)

  6. Browne, P., Ruger, S., Xu, L.-Q., Heesch, D.: iBase: Navigating digital library collections. In: Sundaram, H., Smith, M.N.J.R., Rui, Y. (eds.) 5th International Conference Image and Video Retrieval, volume 4071 of Lecture Notes in Computer Science, pp. 510–513. Springer (2006)

  7. Cattelan, R.G., Teixeira, C., Goularte, R., Pimentel, M.G.C.: Watch-and-comment as a paradigm toward ubiquitous interactive video editing. ACM Trans. Multimed. Comput. Commun. Appl. (TOMCCAP) 4(4) (2008)

  8. Cesar, P., Bulterman, D.C.A., Jansen, J., Geerts, D., Knoche, H., Seager, W.: Fragment, tag, enrich, and send: enhancing the social sharing of videos. ACM. Trans. Multimed. Comput. Commun. Appl. (TOMCCAP) 5(3) (2009)

  9. Cesar, P., Bulterman, D.C.A., Soares, L.F.G.: Human-centered television—directions in interactive digital television research. ACM. Trans. Multimed. Comput. Commun. Appl. (TOMCCAP) 4(4) (2008)

  10. Deerwester, S., Dumais, S.T., Landauer, T., Furnas, G., Harshman, R.: Indexing by latent semantic analysis. J. Soc. Inf. Sci. 41(6), 391–407 (1990)

    Article  Google Scholar 

  11. Forsyth, D.A., Fleck, M.M.: Automatic detection of human nudes. International Int. J. Comput. Vis. 32, 63–77 (1999)

    Article  Google Scholar 

  12. Goldberg, D.E.: Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, Reading, MA (1989)

    MATH  Google Scholar 

  13. Gottlieb, C.C., Kreyszig, H.E.: Texture descriptors based on co-occurrences matrices. Comput. Vis. Graph. Image. Process. 51 (1990)

  14. Goularte, R., Camacho-Guerrero, J.A., Inacio Jr., V.R., Cattelan, R.G., Pimentel, M.G.C.: M4Note: a multimodal tool for multimedia annotations. In: Proceedings of WebMedia and La-Web 2004 Joint Conference—10th Brazilian Symposium on Multimedia and the Web and 2nd Latin American Web Congress (La-Webmedia 2004) (2004)

  15. Goularte, R., Pimentel, M.G.C., Moreira, E.S.: Context-aware support in structured documents for interactive-TV. Multimed. Syst. 11(4), 367–382 (2006)

    Article  Google Scholar 

  16. Halpin, H., Robu, V., Shepherd, H.: The complex dynamics of collaborative tagging. In: Proceedings of the 16th International Conference on World Wide Web, Banff, Alberta, Canada (2007)

  17. Heckner, M., Neubauer, T., Wolff, C.: Tree, funny, to_read, google: what are tags supposed to achieve? A comparative analysis of user keywords for different digital resource types. In: Proceeding of the 2008 ACM Workshop on Search in Social Media, Napa Valley, California, USA (2008)

  18. Holland, J.H.: Adaptation in natural and artificial systems. MIT Press, Michigan (1979)

    Google Scholar 

  19. Joachims, T.: A statistical learning model of text classification for support vector machines. In: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 128–136 (2001)

  20. Kolekar, M.H., Sengupta, S.: A hierarchical framework for generic sports video classification. In: Narayanan, P., Nayar, S.K., Shum, H.-Y. (eds.) 7th Asian Conference on Computer Vision, volume 3852 of Lecture Notes in Computer Science, pp. 633–642 (2006)

  21. Kyperountas, M., Kotropoulos, C., Pitas, I.: Enhanced eigen-audioframes for audiovisual scene change detection. IEEE. Trans. Multimed. 9(4), 785–797 (2007)

    Article  Google Scholar 

  22. Larsson, H., Lindstedt, I., Löwgren, J., Reimer, B., Topgaard, R.: From time-shift to shape-shift: towards nonlinear production and consumption of news. In: EuroITV, pp. 30–39 (2008)

  23. Lee, W., Kim, H., Kang, H., Lee, J., Kim, Y., Jeon, S.: Video cataloging system for real-time scene change detection of news video. Combinatorial Image Analysis, pp. 705–715 (2005)

  24. Li, Y., Narayanan, S., Kuo, C.C.J.: Content-based movie analysis and indexing based on audiovisual cues. IEEE. Trans. Circuits. Syst. Video Technol. 14(8), 1073–1085 (2004)

    Article  Google Scholar 

  25. Macedo, A.A., Guerrero, J.A.C., Pimentel, M.G.C.: A Bilingual Linking Service for the Web. In Consens, M., Navarro, G., editors, 12th International Conference, SPIRE 2005, volume 3772 of Lecture Notes in Computer Science, pp. 45–48 (2005)

  26. Makhoul, J., Kubala, F., Schwartz, R., Weischedel, R.: Performance measures for information extraction. In: Proceedings of DARPA Broadcast News Workshop (1999)

  27. Manzato, M.G., Goularte, R.: Supporting multimedia recommender systems with peer-level annotations. In: Proceedings of the XV Brazilian Symposium on Multimedia and the Web (WebMedia’09), pp. 1–8, Fortaleza, CE, Brazil (2009)

  28. Manzato, M.G., Macedo, A.A., Goularte, R.: Evaluation of video news classification techniques for automatic content personalization. Int. J. Adv. Media. Commun. 3(4), 383–403 (2009)

    Article  Google Scholar 

  29. Masthoff, J.: Group modeling: selecting a sequence of television items to suit a group of viewers. User. Model. User. Adapt. Interact. 14, 37–85 (2004)

    Article  Google Scholar 

  30. Mehtre, B.M., Kankanhalli, M.S., Lee, W.F.: Shape measures for content based image retrieval: a comparison. Inf. Process. Manag. 33, 319–337 (1997)

    Article  Google Scholar 

  31. Mojsilovic, A., Kovacevic, J., Hu, J., Safranek, R.J., Ganapathy, S.K.: Matching and retrieval based on the vocabulary and grammar of color patterns. IEEE. Trans. Image. Process. 9, 38–54 (2000)

    Article  Google Scholar 

  32. Mori, S., Nishida, H., Yamada, H.: Optical character recognition. John Wiley and Sons, New York (1999)

    Google Scholar 

  33. Mundur, P., Rao, Y., Yesha, Y.: Keyframe-based video summarization using Delaunay clustering. Int. J. Digit. Libr. 6(2), 219–232 (2006)

    Article  Google Scholar 

  34. Nitta, N., Babaguchi, N.: Automatic story segmentation of closed-caption text for semantic content analysis of broadcasted sports video. In: Proceedings of the International Workshop on Multimedia Information Systems, pp. 110–116, Arizona, USA (2002)

  35. Quellec, G., Lamard, M., Cazuguel, G., Cochener, B., Roux, C.: Adaptive nonseparable wavelet transform via lifting and its application to content-based image retrieval. IEEE. Trans. Image. Process. 19(1), 25–35 (2010)

    Article  Google Scholar 

  36. Randen, T., Husoy, J.H.: Filtering for texture classification: a comparative study. IEEE. Trans. Pattern Anal. Mach. Intell. 21, 291–310 (1999)

    Article  Google Scholar 

  37. Rosin, P.L.: Edges: saliency measures and automatic thresholding. Mach. Vis. Appl. 9, 139–159 (1997)

    Article  Google Scholar 

  38. Salton, G., Buckley, C.: Term-weighting approaches in automatic text retrieval. Inf. Process. Manag. 24(5), 513–523 (1988)

    Article  Google Scholar 

  39. Samet, H., Soffer, A.: MARCO: map retrieval by content. IEEE. Trans. Pattern. Anal. Mach. Intell. 18, 783–798 (1996)

    Article  Google Scholar 

  40. Smeaton, A.F.: Techniques used and open challenges to the analysis, indexing and retrieval of digital video. Inf. Syst. 32, 545–559 (2007)

    Google Scholar 

  41. Smeaton, A.F., Gurrin, C., Lee, H., McDonald, K., Murphy, N., O’Connor, N.E., Wilson, D., O’Sullivan, D., Smyth, B.: The Físchlár-news-stories system: personalised access to an archive of TV news. In: Fluhr, C., Grefenstette, G., Croft, W.B. (eds.) RIAO, pp. 3–17. CID (2004)

  42. Smeulders, A.W.M., Worring, M., Santini, S., Gupta, A., Jain, R.: Content-based image retrieval at the end of the early years. IEEE. Trans. Pattern Anal. Mach. Intell. 22(12), 1349–1380 (2000)

    Article  Google Scholar 

  43. Swain, M.J., Ballard, B.H.: Color Indexing. Int. J. Comput. Vis. 7, 11–32 (1991)

    Article  Google Scholar 

  44. Tan, Y.P., Saur, D.D., Kulkarni, S.R., Ramadge, P.J.: Rapid estimation of camera motion from compressed video with application to video annotation. IEEE. Trans. Circuits. Syst. Video. Technol. 10(1), 133–146 (2000)

    Article  Google Scholar 

  45. Venkatesh, S., Adams, B., Phung, D., Dorai, C., Farrell, R.G., Agnihotri, L., Dimitrova, N.: “You Tube and I Find”—personalizing multimedia content access. Proc. IEEE, 96(4), 697–711 (2008)

    Google Scholar 

  46. Wang, S.: A robust CBIR approach using local color histograms. Technical Report TR 01-13, University of Alberta (2001)

  47. Weiser, M.: The computer of the 21st century. Sci. Am. 265(3), 94–104 (1991)

    Article  Google Scholar 

  48. Xiong, Z., Zhou, X.S., Tian, Q., Rui, Y., Huangm, T.S.: Semantic retrieval of video—review of research on video retrieval in meetings, movies and broadcast news, and sports. IEEE. Signal. Process. Mag. 23(2), 18–27 (2006)

    Article  Google Scholar 

  49. Yi, H., Rajan, D., Chia, L.T.: Semantic video indexing and summarization using subtitles. In: Aizawa, K., Nakamura, Y., Satoh, S. (eds.) 5th Pacific Rim Conference on Multimedia, volume 3331 of Lecture Notes in Computer Science, pp. 634–641 (2004)

  50. Yu, F., Chang, E., Xu, Y.-Q., Shum, H.-Y.: Emotion detection from speech to enrich multimedia content. In: Shum, H.-Y., Liao, M., Chang, S.-F. (eds.) Second IEEE Pacific Rim Conference on Multimedia Beijing, volume 2195 of Lecture Notes in Computer Science, pp. 550–557 (2001)

  51. Zhang, D., Lu, G.: Evaluation of similarity measurement for image retrieval. In: Proceedings of the 2003 International Conference on Neural Networks and Signal Processing, volume 2, pp. 928–931, December (2003)

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Acknowledgments

We would like to thank the valuable contributions from the CWI team, in particular Pablo Cesar, Dick Bulterman and colleagues. This work was sponsored by UOL (http://www.uol.com.br), through its UOL Bolsa Pesquisa program, process number 20090205103800. We also would like to thank the financial support from CWI, UOL, CNPq and FAPESP.

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  1. Mathematics and Computing Institute, University of São Paulo, Av. Trabalhador Sancarlense, 400, PO Box 668, São Carlos, SP, 13560-970, Brazil

    Marcelo G. Manzato, Danilo B. Coimbra & Rudinei Goularte

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  1. Marcelo G. Manzato
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  3. Rudinei Goularte
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Correspondence to Marcelo G. Manzato.

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Manzato, M.G., Coimbra, D.B. & Goularte, R. An enhanced content selection mechanism for personalization of video news programmes. Multimedia Systems 17, 19–34 (2011). https://doi.org/10.1007/s00530-010-0204-y

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