A static video summarization method based on hierarchical clustering

  • Authors:

  • Silvio Jamil F. Guimarães;Willer Gomes

  • Affiliations:

  • Audio-Visual Information Processing Laboratory, Institute of Informatics, Pontifícia Universidade Católica de Minas Gerais, Belo Horizonte, MG, Brazil;Audio-Visual Information Processing Laboratory, Institute of Informatics, Pontifícia Universidade Católica de Minas Gerais, Belo Horizonte, MG, Brazil

  • Venue:
  • CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
  • Year:
  • 2010

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Abstract

Video summarization is a simplification of video content for compacting the video information. The video summarization problem can be transformed to a clustering problem, in which some frames are selected to saliently represent the video content. In this work, we use a graph-theoretic divisive clustering algorithm based on construction of a minimum spanning tree to select video frames without segmenting the video into shots or scenes. Experimental results provides a visually comparison between the new approach and other popular algorithms from the literature, showing that the new algorithm is robust and efficient.