An Integrated Scheme for Automated Video Abstraction based on Unsupervised Cluster-Validity Analysis

  • Hong-Jiang Zhang ,
  • Alan Hanjalic

Published by Institute of Electrical and Electronics Engineers, Inc.

Publication

Key frames and previews are two forms of a video abstract, widely used for various applications in video browsing and retrieval systems. We propose in this paper a novel method for generating these two abstract forms for an arbitrary video sequence. The underlying principle of the proposed method is the removal of the visual-content redundancy among video frames. This is done by first applying multiple partitional clustering to all frames of a video sequence, and then selecting the most suitable clustering option(s) by an unsupervised cluster-validity procedure. In the last step, key frames are selected as centroids of obtained optimal clusters. Video shots, to which key frames belong, are concatenated to form the preview sequence.