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

Shih Fu Chang, William Chen, Horace J. Meng, Hari Sundaram, Di Zhong

Research output: Contribution to journalArticlepeer-review


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 (demo available at http://www.ctr.columbia.edu/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.

Original languageEnglish (US)
Pages (from-to)602-615
Number of pages14
JournalIEEE Transactions on Circuits and Systems for Video Technology
Issue number5
StatePublished - 1998
Externally publishedYes


  • Content based
  • Information retreival
  • Object oriented
  • Spatiotemporal
  • Video query

ASJC Scopus subject areas

  • Media Technology
  • Electrical and Electronic Engineering


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