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A Social Network Based Collaborative Video Story Composition Platform

  • Chen Wang
  • Meng Meng
  • Xiangmin Zhou
  • Rajiv Ranjan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7759)

Introduction

There is a large number of videos produced and stored in data repositories on a daily basis. Story-telling is a common use-case for using these videos where a user composes a set of videos together to tell a story, either for learning purposes or sharing experiences. For example, a news editor may search and compose story based on video collected from multiple private and public repositories; an instructor may produce teaching materials using a set of publicly available video clips. Existing search engines have limitation on identifying useful video contents for users with different needs [2]. For a user who attempts to compile a story using a variety of videos, there are a few challenges with existing technologies. A search engine often returns a long list of videos that are relevant to the keywords the user enters into the search engine. How the videos in the list are suitable for the story line requires the user’s further investigation and the amount of work involved often overwhelms the user considering the number of videos returned by a search engine. It is often the case that the highly ranked videos are not the most appropriate ones for a story line under composing. In addition, videos are not organized in a structured manner based on the content, which makes identifying videos that match the story topic difficult and time consuming.

Keywords

Search Engine Data Repository Story Line Recommendation Service Author Sign 
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.

References

  1. 1.
    Hammer-Lahav, E., Recordon, D., Hardt, D.: The oauth 2.0 authorization protocol. Network Working Group Internet-Drafts, http://tools.ietf.org/pdf/draft-ietf-oauth-v2-12.pdf
  2. 2.
    Hong, R., Tang, J., Tan, H.-K., Ngo, C.-W., Yan, S., Chua, T.-S.: Beyond search: Event-driven summarization for web videos. ACM Trans. Multimedia Comput. Commun. Appl. 7(4), 35:1–35:18 (2011)CrossRefGoogle Scholar
  3. 3.
    Wu, X., Ngo, C.-W., Li, Q.: Threading and autodocumenting news videos: a promising solution to rapidly browse news topics. IEEE Signal Processing Magazine 23(2), 59–68 (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Chen Wang
    • 1
  • Meng Meng
    • 1
  • Xiangmin Zhou
    • 1
  • Rajiv Ranjan
    • 1
  1. 1.Information Engineering LabCSIRO ICT CentreAustralia

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