MultiView: Multilevel video content representation and retrieval

J. Fan, W. G. Aref, Ahmed Elmagarmid, M. S. Hacid, M. S. Marzouk, X. Zhu

Research output: Contribution to journalArticle

43 Citations (Scopus)


In this article, several practical algorithms are proposed to support content-based video analysis, modeling, representation, summarization, indexing, and access. First, a multilevel video database model is given. One advantage of this model is that it provides a reasonable approach to bridging the gap between low-level representative features and high-level semantic concepts from a human point of view. Second, several model-based video analysis techniques are proposed. In order to detect the video shots, we present a novel technique, which can adapt the threshold for scene cut detection to the activities of variant videos or even different video shots. A seeded region aggregation and temporal tracking technique is proposed for generating the semantic video objects. The semantic video scenes can then be generated from these extracted video access units (e.g., shots and objects) according to some domain knowledge. Third, in order to categorize video contents into a set of semantic clusters, an integrated video classification technique is developed to support more efficient multilevel video representation, summarization, indexing, and access techniques.

Original languageEnglish
Pages (from-to)895-908
Number of pages14
JournalJournal of Electronic Imaging
Issue number4
Publication statusPublished - 1 Oct 2001
Externally publishedYes


ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Atomic and Molecular Physics, and Optics
  • Computer Vision and Pattern Recognition

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