A logical framework for visual information modeling and management

Youngchoon Park, Pankoo Kim, Forouzan Golshani, Sethuraman Panchanathan

Research output: Contribution to journalArticlepeer-review


A unified semantic visual data-modeling framework is presented in the paper. In the proposed model, an extended conceptual graph is proposed as an annotation mechanism of a user's perceptual understanding of video objects, activities, and events. A precise definition of the term "domain knowledge" in visual information processing is presented. A conceptual structure, associated terms, visual feature extraction methods, and a set of constraints in feature extraction are considered as domain information. The proposed visual data model has six different abstraction layers. A higher level is more abstracted and more semantically summarized. A polygon-based bounding volume is used in video object approximation in space and time. We use a bounding volume in motion trajectory representation, rather than motion vectors. This model allows simultaneous access of both temporal and spatial information. The proposed model may be used as a referencing framework for various visual information management systems' developments.

Original languageEnglish (US)
Pages (from-to)271-291
Number of pages21
JournalCircuits, Systems, and Signal Processing
Issue number2
StatePublished - 2001


  • Content-based multimedia information retrieval
  • Semantic data modeling
  • Visual information retrieval

ASJC Scopus subject areas

  • Signal Processing
  • Applied Mathematics


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