Model-based video classification toward hierarchical representation, indexing and access

J. Fan, X. Zhu, M. S. Hacid, Ahmed Elmagarmid

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In this paper, we develop a content-based video classification approach to support semantic categorization, high-dimensional indexing and multi-level access. Our contributions are in four points: (a) We first present a hierarchical video database model that captures the structures and semantics of video contents in databases. One advantage of this hierarchical video database model is that it can provide a framework for automatic mapping from high-level concepts to low-level representative features. (b) We second propose a set of useful techniques for exploiting the basic units (e.g., shots or objects) to access the videos in database. (c) We third suggest a learning-based semantic classification technique to exploit the structures and semantics of video contents in database. (d) We further develop a cluster-based indexing structure to both speed-up query-by-example and organize databases for supporting more effective browsing. The applications of this proposed multi-level video database representation and indexing structures for MPEG-7 are also discussed.

Original languageEnglish
Pages (from-to)97-120
Number of pages24
JournalMultimedia Tools and Applications
Volume17
Issue number1
DOIs
Publication statusPublished - 1 May 2002
Externally publishedYes

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Keywords

  • Video analysis
  • Video database
  • Video retrieval

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Information Systems
  • Computer Graphics and Computer-Aided Design
  • Software
  • Theoretical Computer Science
  • Computational Theory and Mathematics

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