Research on High-Level Semantic Image Retrieval

Abstract:

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This paper presented the key problems to shorten “semantic gap” between low-level visual features and high-level semantic features to implement high-level semantic image retrieval. First, introduced ontology based semantic image description and semantic extraction methods based on machine learning. Then, illustrated image grammar on the high-level semantic image understanding and retrieval, and-or graph and context based methods of semantic image. Finally, we discussed the development directions and research emphases in this field.

Info:

Periodical:

Advanced Materials Research (Volumes 268-270)

Edited by:

Feng Xiong

Pages:

1427-1432

DOI:

10.4028/www.scientific.net/AMR.268-270.1427

Citation:

C. Y. Ri and M. Yao, "Research on High-Level Semantic Image Retrieval", Advanced Materials Research, Vols. 268-270, pp. 1427-1432, 2011

Online since:

July 2011

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Price:

$35.00

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