The increasing need of video based applications issues the importance of parsing and organizing the content in videos. However, the accurate understanding and manag- ing video contents at the semantic level is still i...The increasing need of video based applications issues the importance of parsing and organizing the content in videos. However, the accurate understanding and manag- ing video contents at the semantic level is still insufficient. The semantic gap between low level features and high level semantics cannot be bridged by manual or semi-automatic methods. In this paper, a semantic based model named video structural description （VSD） for representing and organizing the content in videos is proposed. Video structural descrip- tion aims at parsing video content into the text information, which uses spatiotemporal segmentation, feature selection, object recognition, and semantic web technology. The pro- posed model uses the predefined ontologies including con- cepts and their semantic relations to represent the contents in videos. The defined ontologies can be used to retrieve and organize videos unambiguously. In addition, besides the de- fined ontologies, the semantic relations between the videos are mined. The video resources are linked and organized by their related semantic relations.展开更多
文摘The increasing need of video based applications issues the importance of parsing and organizing the content in videos. However, the accurate understanding and manag- ing video contents at the semantic level is still insufficient. The semantic gap between low level features and high level semantics cannot be bridged by manual or semi-automatic methods. In this paper, a semantic based model named video structural description （VSD） for representing and organizing the content in videos is proposed. Video structural descrip- tion aims at parsing video content into the text information, which uses spatiotemporal segmentation, feature selection, object recognition, and semantic web technology. The pro- posed model uses the predefined ontologies including con- cepts and their semantic relations to represent the contents in videos. The defined ontologies can be used to retrieve and organize videos unambiguously. In addition, besides the de- fined ontologies, the semantic relations between the videos are mined. The video resources are linked and organized by their related semantic relations.
