DocumentCode :
2448516
Title :
Brief survey on image semantic analysis and understanding
Author :
Xie, Zhao ; Gao, Jun ; Wu, Kewei ; Zhang, Jun
Author_Institution :
Sch. of Comput. & Inf., Hefei Univ. of Technol., Hefei, China
fYear :
2011
fDate :
14-16 Oct. 2011
Firstpage :
179
Lastpage :
183
Abstract :
Semantic issues are highly concerned with high-level interpretation in image understanding, which include text-image gap and its own affinity. Concentrating on text-formatting with entities in images, three sophisticated methodologies are roundly reviewed as generative, discriminative and descriptive grammar on the basis of contextual features. The following objective benchmark for visual words is also directly presented for semantic coherency. Finally, the summarized directions on semantics in image understanding are discussed intensively for further researches.
Keywords :
computer vision; contextual features; descriptive grammar; discriminative grammar; high level interpretation; semantic coherency; text-formatting; text-image gap; Benchmark testing; Computational modeling; Computer vision; Educational institutions; Pattern recognition; Semantics; Visualization; Data-and-knowledge coherence; Image understanding; Semantic gap;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Soft Computing and Pattern Recognition (SoCPaR), 2011 International Conference of
Conference_Location :
Dalian
Print_ISBN :
978-1-4577-1195-4
Type :
conf
DOI :
10.1109/SoCPaR.2011.6089136
Filename :
6089136
Link To Document :
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