Video Skimming and Characterization through the Combination of Image and Language Understanding Techniques

  • Authors:

  • Michael A. Smith

  • Affiliations:

  • -

  • Venue:
  • CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
  • Year:
  • 1997

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Abstract

Digital video is rapidly becoming important for education, entertainment, and a host of multimedia applications. With the size of the video collections growing to thousands of hours, technology is needed to effectively browse seg ments in a short time without losing the content of the video. We propose a method to extract the significant audio and video information and create a "skim" video which represents a very short synopsis of the original. The goal of this work is to show the utility of integrating lan guage and image understanding techniques for video skimming by extraction of significant information, such as specific objects, audio keywords and relevant video struc ture. The resulting skim video is much shorter, where com paction is as high as 20:1, and yet retains the essential content of the original segment.