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Browsing Linked Video Collections for Media Production

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 8326)

Abstract

This paper describes a video browsing tool for media (post-) production, enabling users to efficiently find relevant media items for redundant and sparsely annotated content collections. Users can iteratively cluster the content set by different features, and restrict the content set by selecting a subset of clusters. In addition to clustering by features, similarity search by different features is supported, and a set of linked video segments can be explored for a segment of interest. Desktop and Web-based variants of the user interface, including temporal preview functionality, are available.

Keywords

  • Similarity Search
  • Result List
  • Result Segment
  • Content Collection
  • Light Table

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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  • DOI: 10.1007/978-3-319-04117-9_47
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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)

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  2. Bailer, W., Weiss, W., Kienast, G., Thallinger, G., Haas, W.: A video browsing tool for content management in post-production. International Journal of Digital Multimedia Broadcasting (March 2010)

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  3. Lokaj, M., Stiegler, H., Bailer, W.: The Search and Hyperlinking Task at MediaEval 2013. In: MediaEval 2013 Workshop, Barcelona, Spain, October 18-19 (2013)

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  4. Lowe, D.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60(2), 91–110 (2004)

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© 2014 Springer International Publishing Switzerland

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Bailer, W., Weiss, W., Schober, C., Thallinger, G. (2014). Browsing Linked Video Collections for Media Production. 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 8326. Springer, Cham. https://doi.org/10.1007/978-3-319-04117-9_47

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  • DOI: https://doi.org/10.1007/978-3-319-04117-9_47

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-04116-2

  • Online ISBN: 978-3-319-04117-9

  • eBook Packages: Computer ScienceComputer Science (R0)