Concept-oriented indexing of video databases: Toward semantic sensitive retrieval and browsing

Jianping Fan, Hangzai Luo, Ahmed K. Elmagarmid

Research output: Contribution to journalArticle

58 Citations (Scopus)

Abstract

Digital video now plays an important role in medical education, health care, telemedicine and other medical applications. Several content-based video retrieval (CBVR) systems have been proposed in the past, but they still suffer from the following challenging problems: semantic gap, semantic video concept modeling, semantic video classification, and concept-oriented video database indexing and access. In this paper, we propose a novel framework to make some advances toward the final goal to solve these problems. Specifically, the framework includes: 1) a semantic-sensitive video content representation framework by using principal video shots to enhance the quality of features; 2) semantic video concept interpretation by using flexible mixture model to bridge the semantic gap; 3) a novel semantic video-classifier training framework by integrating feature selection, parameter estimation, and model selection seamlessly in a single algorithm; and 4) a concept-oriented video database organization technique through a certain domain-dependent concept hierarchy to enable semantic-sensitive video retrieval and browsing.

Original languageEnglish
Pages (from-to)974-992
Number of pages19
JournalIEEE Transactions on Image Processing
Volume13
Issue number7
DOIs
Publication statusPublished - 1 Jul 2004

    Fingerprint

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

Cite this