Unifying keywords and visual contents in image retrieval

Xiang Sean Zhou; Thomas S. Huang

doi:10.1109/93.998050

Unifying keywords and visual contents in image retrieval

Xiang Sean Zhou, Thomas S. Huang

Research output: Contribution to journal › Article › peer-review

Abstract

The unification of keywords and feature contents for image retrieval is addressed. A seamless joint querying and relevance feedback scheme based on both keywords and low-level visual contents incorporating keyword similarities is proposed. An algorithm for the learning of the word similarity matrix during user interaction is introduced. This learned similarity matrix can be applied for keyword semantic grouping, thesaurus construction, and soft query expansion during intelligent image retrieval.

Original language	English (US)
Pages (from-to)	23-33
Number of pages	11
Journal	IEEE Multimedia
Volume	9
Issue number	2
DOIs	https://doi.org/10.1109/93.998050
State	Published - Apr 2002
Externally published	Yes

ASJC Scopus subject areas

Software
Signal Processing
Media Technology
Hardware and Architecture
Computer Science Applications

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10.1109/93.998050

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abstract = "The unification of keywords and feature contents for image retrieval is addressed. A seamless joint querying and relevance feedback scheme based on both keywords and low-level visual contents incorporating keyword similarities is proposed. An algorithm for the learning of the word similarity matrix during user interaction is introduced. This learned similarity matrix can be applied for keyword semantic grouping, thesaurus construction, and soft query expansion during intelligent image retrieval.",

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Unifying keywords and visual contents in image retrieval

Abstract

ASJC Scopus subject areas

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