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
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;
Conference_Titel :
Computer Distributed Control and Intelligent Environmental Monitoring (CDCIEM), 2012 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-1-4673-0458-0
DOI :
10.1109/CDCIEM.2012.109
