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Innovative Internet video consuming based on media analysis techniques

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Abstract

Internet video is becoming more and more popular in consuming field. The increasing of video data volumes requires some innovative means to enrich the video consuming experiences. Multimedia analysis is the key means, which can provide conveniences to both Internet video providers and consumers. This paper reviews the progress of media analysis techniques, investigates typical innovative Internet video services based on media analysis, introduces some innovative user experiences based on media analysis, and presents some open issues and potential research topics in media analysis and the related applications in Internet video services. We hope the paper provides valuable information to the researchers, engineers or decision-makers working in the fields of Internet video and media analysis.

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References

  1. Internet video: http://en.wikipedia.org/wiki/Internet_video. Accessed by September 10, 2009.

  2. Ardissono, L., Kobsa, A., & Maybury, M. T. (Eds.) (2004). Book series: human-computer interaction series : Vol. 6. Personalized digital television: targeting programs to individual viewers. Berlin: Springer, 331 pp.

    Google Scholar 

  3. PHAROS (Platform for searcHing of Audiovisual Resources across Online Spaces), an Integrated Project co-financed by the European Union. http://www.pharos-audiovisual-search.eu/. Accessed by September 10, 2009.

  4. Multimedia Understanding through Semantics, Computation and Learning (MUSCLE). http://muscle.ercim.org/. Accessed by September 10, 2009.

  5. Kawai, Y., Sumiyoshi, H., & Yagi, N. (2007). Shot boundary detection at TRECVID 2007. In Proc. of TRECVID Workshop.

    Google Scholar 

  6. Ekin, A., Tekalp, A. M., & Mehrotra, R. (2003). Automatic soccer video analysis and summarization. IEEE Transactions on Image Processing, 12(7), 796–807.

    Article  Google Scholar 

  7. TREC Video Retrieval Evaluation, http://www-nlpir.nist.gov/projects/trecvid/. Accessed by September 10, 2009.

  8. Papadopoulos, G. T., Saathoff, C., Grzegorzek, M., Mezaris, V., Kompatsiaris, I., Staab, S., & Strintzis, M. G. (2009). Comparative evaluation of spatial context techniques for semantic image analysis. In 10th workshop on image analysis for multimedia interactive services (WIAMIS’09) (pp. 161–164). May 2009.

    Chapter  Google Scholar 

  9. Chen, Z.-S., & Jang, J.-S. (2009). On the use of anti-word models for audio music annotation and retrieval. IEEE Transactions on Audio, Speech and Language Processing, 17(8), 1547–1556.

    Article  Google Scholar 

  10. Dang, H. T., & Owczarzak, K. (2008). Overview of the TAC 2008 update summarization task. In 2008 text analysis conference (TAC 2008). Gaithersburg, Maryland USA, November 17–19, 2008.

    Google Scholar 

  11. Zhang, Y.-J. (2006). Advances in image and video segmentation. Hershey: Idea Group Pub.

    Google Scholar 

  12. Leexoo video search. http://adgrid.leexoo.com/. Accessed by September 10, 2009.

  13. Newscloud. http://mediawatch.afp.com/?post/2009/04/04/Orange-editeur-de-reseaux-%3A-la-cible-cest-Google. Accessed by September 10, 2009.

  14. Iulio, M. D., & Messina, A. (2008). Use of probabilistic clusters supports for broadcast news segmentation. In Proceeding of 19th international conference on database and expert systems application (pp. 600–604).

    Chapter  Google Scholar 

  15. Blinkx. http://www.blinkx.com/. Accessed by September 10, 2009.

  16. Bing. http://cn.bing.com/. Accessed by September 10, 2009.

  17. YouTube. http://www.youtube.com/. Accessed by September 10, 2009.

  18. Videosphere. http://www.netexplorateur.org/videospheres/english/. Accessed by September 10, 2009.

  19. Mfula, H. (2008). Highlights extraction from unscripted video. T61.6030, Multimedia retrieval seminar presentation 04.04.2008.

  20. Joyce, R. A., & Liu, B. (2006). Temporal segmentation of video using frame and histogram space. IEEE Transactions on Multimedia, 8(1), 130–140.

    Article  Google Scholar 

  21. Over, P., Awad, G., Rose, T., Fiscus, J., Kraaij, W., & Smeaton, A. F. (2008). TRECVID 2008-goals, tasks, data, evaluation mechanisms and metrics. In ACM multimedia 2008. Vancouver, Canada, October, 2008.

    Google Scholar 

  22. 2424actu. http://www.2424actu.fr/actualite-la-une. Accessed by September 10, 2009.

  23. Voxalead News. http://voxaleadnews.labs.exalead.com/. Accessed by September 10, 2009.

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Authors and Affiliations

  1. France Telecom R&D (Orange Labs) Beijing, Beijing, 100080, China

    Shiguo Lian

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  1. Shiguo Lian
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Correspondence to Shiguo Lian.

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Lian, S. Innovative Internet video consuming based on media analysis techniques. Electron Commer Res 11, 75–89 (2011). https://doi.org/10.1007/s10660-010-9066-9

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  • DOI: https://doi.org/10.1007/s10660-010-9066-9

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