Towards retrieval of visual information based on the semantic models

Youngchoon Park, Pankoo Kim, Wonpil Kim, Jeongjun Song, Sethuraman Panchanathan

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Most users want to find visual information based on the semantics of visual contents such as a name of person and an action happening in a scene. However, techniques for content-based image or video retrieval are not mature enough to recognize visual semantic completely. This paper concerns the problem of automated visual content classification that allows semantic exploration of the visual information. To enable semantic based image or visual object retrieval, we propose a new image representation scheme called visual context descriptor (VCD) that is a multidimensional vector in which each element represents the frequency of a unique visual property of an image or a region. VCD utilizes the predetermined quality dimensions (i.e., types of features and quantization levels) and semantic model templates mined in priori. Techniques for creating symbolic representation (called visual term) of visual content and semantic model profile mining and matching have also been explored. The proposed model classification technique utilizes contextual relevance of a visual term to a target semantic class in visual object discrimination. Contextual relevance of a visual cue to a semantic class is determined by using correlation analysis of ground truth samples.

Original languageEnglish (US)
Title of host publicationDatabase and Expert Systems Applications - 13th International Conference, DEXA 2002, Proceedings
EditorsAbdelkader Hameurlain, Rosiner Cicchetti, Roland Traunmuller
PublisherSpringer Verlag
Number of pages10
ISBN (Print)3540441263, 9783540441267
StatePublished - 2002
Event13th International Conference on Database and Expert Systems Applications, DEXA 2002 - Aix-en-Provence, France
Duration: Sep 2 2002Sep 6 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other13th International Conference on Database and Expert Systems Applications, DEXA 2002

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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