Semantic video model for content-based retrieval

Jia Ling Koh*, Chin Sung Lee, Arbee L.P. Chen

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

12 Citations (Scopus)


Traditional research on video data retrieval follows two general approaches. One is based on text annotation and the other on content-based comparison. However, these approaches do not fully make use of the meaning implied in a video stream. To improve these approaches, a semantic video model cooperated with a knowledge database is studied. In this paper, we propose a new semantic video model and focus on presenting the semantic meaning implied in a video. According to the granularity of the meaning implied in a video, a five-level layered structure to model a video stream is proposed. A mechanism is also provided to construct the five levels based on the knowledge categories defined in the knowledge database. The five-level layered structure consists of raw-data levels and semantic-data levels. A uniform semantics representation is proposed to represent the semantic-data levels. This uniform semantics representation allows measuring the similarity of two video streams with different duration. Then an interactive interface can provide browsing and querying video data efficiently through the uniform semantics representation.

Original languageEnglish
Number of pages7
Publication statusPublished - 1999
EventProceedings of the 1999 6th International Conference on Multimedia Computing and Systems - IEEE ICMCS'99 - Florence, Italy
Duration: 1999 Jun 71999 Jun 11


ConferenceProceedings of the 1999 6th International Conference on Multimedia Computing and Systems - IEEE ICMCS'99
CityFlorence, Italy

ASJC Scopus subject areas

  • General Computer Science
  • General Engineering


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