A fully automated content-based video search engine supporting spatiotemporal queries

  • Authors:

  • Shih-Fu Chang;W. Chen;H. J. Meng;H. Sundaram;Di Zhong

  • Affiliations:

  • Dept. of Electr. Eng., Columbia Univ., New York, NY;-;-;-;-

  • Venue:
  • IEEE Transactions on Circuits and Systems for Video Technology
  • Year:
  • 1998

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Abstract

The rapidity with which digital information, particularly video, is being generated has necessitated the development of tools for efficient search of these media. Content-based visual queries have been primarily focused on still image retrieval. In this paper, we propose a novel, interactive system on the Web, based on the visual paradigm, with spatiotemporal attributes playing a key role in video retrieval. We have developed innovative algorithms for automated video object segmentation and tracking, and use real-time video editing techniques while responding to user queries. The resulting system, called VideoQ , is the first on-line video search engine supporting automatic object-based indexing and spatiotemporal queries. The system performs well, with the user being able to retrieve complex video clips such as those of skiers and baseball players with ease