DocumentCode
1678287
Title
Narrowing Semantic Gap in Content-based Image Retrieval
Author
Yang, Jun ; Zhu, Shi-jiao
Author_Institution
Sch. of Comput. & Inf. Eng., Shanghai Univ. of Electr. Power, Shanghai, China
fYear
2012
Firstpage
433
Lastpage
438
Abstract
Due to the low-level image features it utilizes, the semantic gap problem is hard to bridge and performance of CBIR systems is still far away from users\´ expectation. Image annotation, region-based image retrieval and relevance feedback are three main approaches for narrowing the "semantic gap". In this paper, recent development in these fields are reviewed and some future directions are proposed in the end.
Keywords
content-based retrieval; image retrieval; relevance feedback; CBIR systems; content-based image retrieval; image annotation; region-based image retrieval; relevance feedback; semantic gap problem; Feature extraction; Image retrieval; Image segmentation; Radio frequency; Semantics; Support vector machines; Visualization; Content-based Image Retrieval; Image Annotation; Region-based Image Retrieval; Relevance Feedback;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Distributed Control and Intelligent Environmental Monitoring (CDCIEM), 2012 International Conference on
Conference_Location
Hunan
Print_ISBN
978-1-4673-0458-0
Type
conf
DOI
10.1109/CDCIEM.2012.109
Filename
6178507
Link To Document