Category-Specific Video Summarization

  • Danila Potapov
  • Matthijs Douze
  • Zaid Harchaoui
  • Cordelia Schmid
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8694)

Abstract

In large video collections with clusters of typical categories, such as “birthday party” or “flash-mob”, category-specific video summarization can produce higher quality video summaries than unsupervised approaches that are blind to the video category.

Given a video from a known category, our approach first efficiently performs a temporal segmentation into semantically-consistent segments, delimited not only by shot boundaries but also general change points. Then, equipped with an SVM classifier, our approach assigns importance scores to each segment. The resulting video assembles the sequence of segments with the highest scores. The obtained video summary is therefore both short and highly informative. Experimental results on videos from the multimedia event detection (MED) dataset of TRECVID’11 show that our approach produces video summaries with higher relevance than the state of the art.

Keywords

video summarization temporal segmentation video classification 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Danila Potapov
    • 1
  • Matthijs Douze
    • 1
  • Zaid Harchaoui
    • 1
  • Cordelia Schmid
    • 1
  1. 1.InriaFrance

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