DocumentCode
3467509
Title
Semantic Information Extraction of Video Based on Ontology and Inference
Author
Ma, Jie ; Zhang, Jing ; Lu, Hong ; Xue, Xiangyang
Author_Institution
Fudan Univ., Shanghai
fYear
2007
fDate
17-19 Sept. 2007
Firstpage
721
Lastpage
726
Abstract
In this paper, a new ontology-based composite concept detection method is proposed, which adopts Bayesian network to construct the ontology and uses the inference rules to perform the composite concept detection providing the concrete concepts in a phrase of video. Furthermore, the probability instead of binary value is gained through the inference pattern of Bayesian network, which can obtain more precise results. The main contribution of this paper is that semantic concept ontology is constructed using Bayesian network and the constructed ontology represents the hierarchical relationship between the concepts which can be used for inference. The method narrows the influence of "Semantic Gap" in some extent and achieves good performance in composite concept detection.
Keywords
belief networks; inference mechanisms; ontologies (artificial intelligence); semantic networks; statistical distributions; video retrieval; Bayesian network; inference rules; ontology-based composite concept detection method; probability distribution; semantic concept ontology construction; semantic gap; semantic information extraction; semantic network; video retrieval; Airplanes; Bayesian methods; Computer networks; Computer science; Concrete; Data mining; Graphical models; Information retrieval; Ontologies; Videoconference;
fLanguage
English
Publisher
ieee
Conference_Titel
Semantic Computing, 2007. ICSC 2007. International Conference on
Conference_Location
Irvine, CA
Print_ISBN
978-0-7695-2997-4
Type
conf
DOI
10.1109/ICSC.2007.17
Filename
4338415
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