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Creating Summaries from User Videos

  • Michael Gygli
  • Helmut Grabner
  • Hayko Riemenschneider
  • Luc Van Gool
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8695)

Abstract

This paper proposes a novel approach and a new benchmark for video summarization. Thereby we focus on user videos, which are raw videos containing a set of interesting events. Our method starts by segmenting the video by using a novel “superframe” segmentation, tailored to raw videos. Then, we estimate visual interestingness per superframe using a set of low-, mid- and high-level features. Based on this scoring, we select an optimal subset of superframes to create an informative and interesting summary. The introduced benchmark comes with multiple human created summaries, which were acquired in a controlled psychological experiment. This data paves the way to evaluate summarization methods objectively and to get new insights in video summarization. When evaluating our method, we find that it generates high-quality results, comparable to manual, human-created summaries.

Keywords

Video analysis video summarization temporal segmentation 

Supplementary material

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Michael Gygli
    • 1
    • 2
  • Helmut Grabner
    • 1
    • 2
  • Hayko Riemenschneider
    • 1
  • Luc Van Gool
    • 1
    • 3
  1. 1.Computer Vision LaboratoryETH ZurichSwitzerland
  2. 2.upicto GmbHZurichSwitzerland
  3. 3.K.U. LeuvenBelgium

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