Video structural description technology for the new generation video surveillance systems

摘要

The increasing need of video based applications issues the importance of parsing and organizing the content in videos. However, the accurate understanding and managing 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 description aims at parsing video content into the text information, which uses spatiotemporal segmentation, feature selection, object recognition, and semantic web technology. The proposed model uses the predefined ontologies including concepts and their semantic relations to represent the contents in videos. The denned ontologies can be used to retrieve and organize videos unambiguously. In addition, besides the defined ontologies, the semantic relations between the videos are mined. The video resources are linked and organized by their related semantic relations.