Semantic Concept Detection Based on Concept Lattice Rule Reduced by Negative Sample
Yongzhao Zhan · Jisuanji gongcheng · 2011
To mine the rich semantic information in videos,this paper proposes a semantic concept detection method based on concept lattice rules reduced by negative samples.Through analyzing the semantic analysis system based on concept lattice and considering the information of negative samples in training data,it designs an algorithm for extracting semantic rules reduced by negative samples and apples the algorithm in video semantic detection.The low-level features of the video shots are mapped to the low-level semantic features,and the video semantic concept is detected after the semantic classification rules are generated by the proposed method.Experimental results show the feasibility and validity of the method.