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International Conference on Semantic Computing (ICSC 2007)
Semantic Information Extraction of Video Based on Ontology and Inference
Irvine, California
September 17-September 19
ISBN: 0-7695-2997-6
Jie Ma, Fudan University, China
Jing Zhang, East China University of Science & Technology, China
Hong Lu, Member, IEEE; Fudan University, China
Xiangyang Xue, Fudan University, China
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.
Citation:
Jie Ma, Jing Zhang, Hong Lu, Xiangyang Xue, "Semantic Information Extraction of Video Based on Ontology and Inference," icsc, pp.721-726, International Conference on Semantic Computing (ICSC 2007), 2007
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