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Selecting User Generated Content for Use in Media Productions

Part of the Lecture Notes in Computer Science book series (LNISA,volume 9517)

Abstract

This paper describes a video browsing tool for visual media production, enabling users to efficiently find relevant user generated content, while considering its relation to the professional content captured for the production. Users can iteratively cluster the content set by different features, and restrict the content set by selecting a subset of clusters, and perform similarity search. The tool supports metadata captured with the content (e.g., location, device) and provides support for extracting global and local visual features. Content with multiple views is supported.

Keywords

  • Visual Similarity
  • Video Segment
  • User Generate Content
  • Object Trajectory
  • Browse User Interface

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

  1. 1.

    http://www.vlfeat.org.

  2. 2.

    http://www.tosca-mp.eu.

References

  1. Information technology - multimedia content description interface - part 9: Profiles and levels, amendment 1: Extensions to profiles and levels. ISO/IEC 15938–9:2005/Amd1:2012 (2012)

    Google Scholar 

  2. Bailer, W., Weiss, W., Kienast, G., Thallinger, G., Haas, W.: A video browsing tool for content management in postproduction. Int. J. Digital Multimed. Broadcast. 2010, 17 (2010). Article ID 856761. doi:10.1155/2010/856761

    Google Scholar 

  3. Bailer, W., Weiss, W., Schober, C., Thallinger, G.: Browsing linked video collections for media production. In: Gurrin, C., Hopfgartner, F., Hurst, W., Johansen, H., Lee, H., O’Connor, N. (eds.) MMM 2014, Part II. LNCS, vol. 8326, pp. 407–410. Springer, Heidelberg (2014)

    CrossRef  Google Scholar 

  4. Barthel, K.U., Hezel, N., Mackowiak, R.: Graph-based browsing for large video collections. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds.) MMM 2015, Part II. LNCS, vol. 8936, pp. 237–242. Springer, Heidelberg (2015)

    Google Scholar 

  5. Blažek, A., Lokoč, J., Matzner, F., Skopal, T.: Enhanced signature-based video browser. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds.) MMM 2015, Part II. LNCS, vol. 8936, pp. 243–248. Springer, Heidelberg (2015)

    Google Scholar 

  6. Cobârzan, C., Del Fabro, M., Schoeffmann, K.: Collaborative browsing and search in video archives with mobile clients. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds.) MMM 2015, Part II. LNCS, vol. 8936, pp. 266–271. Springer, Heidelberg (2015)

    Google Scholar 

  7. Fassold, H., Wechtitsch, S., Thaler, M., Kozłowski, K., Bailer, W.: Real-time video quality analysis on mobile devices. In: Proceedings of the 7th ACM International Workshop on Mobile Video, pp. 23–24, Portland, March 2015

    Google Scholar 

  8. Hudelist, M.A., Xu, Q.: The multi-stripe video browser for tablets. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds.) MMM 2015, Part II. LNCS, vol. 8936, pp. 272–277. Springer, Heidelberg (2015)

    Google Scholar 

  9. Hürst, W., van de Werken, R., Hoet, M.: A storyboard-based interface for mobile video browsing. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds.) MMM 2015, Part II. LNCS, vol. 8936, pp. 261–265. Springer, Heidelberg (2015)

    Google Scholar 

  10. Jegou, H., Perronnin, F., Douze, M., Sanchez, J., Perez, P., Schmid, C.: Aggregating local image descriptors into compact codes. IEEE Trans. Pattern Anal. Mach. Intell. 34(9), 1704–1716 (2012)

    CrossRef  Google Scholar 

  11. Lowe, D.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)

    CrossRef  Google Scholar 

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Acknowledgments

The research leading to these results has received funding from the European Union’s Seventh Framework Programme (FP7/2007-2013) under grant agreements n\(^\circ \) 215475, “2020 3D Media – Spatial Sound and Vision” (http://www.20203dmedia.eu/), and n\(^\circ \) 287532, “TOSCA-MP - Task-oriented search and content annotation for media production” (http://www.tosca-mp.eu) and n\(^\circ \) 610370, ICoSOLE (“Immersive Coverage of Spatially Outspread Live Events”, http://www.icosole.eu).

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Correspondence to Werner Bailer .

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Bailer, W., Weiss, W., Wechtitsch, S. (2016). Selecting User Generated Content for Use in Media Productions. In: Tian, Q., Sebe, N., Qi, GJ., Huet, B., Hong, R., Liu, X. (eds) MultiMedia Modeling. MMM 2016. Lecture Notes in Computer Science(), vol 9517. Springer, Cham. https://doi.org/10.1007/978-3-319-27674-8_38

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  • DOI: https://doi.org/10.1007/978-3-319-27674-8_38

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