Due to the rapid increase in the amount of available video data, there has been a growing demand for efficient methods to understand and manage the data at the semantic level. In this paper, the V-OWL is proposed with extensions to OWL, which can describe complex video content including temporal-spatial and uncertain relationships. The B-Graph description model based on Bayesian Net is proposed to map the concepts and relationships in V-OWL ontology into the nodes and edges in B-Graph. Video semantic content can be discovered automatically by using existing training and reasoning methods of Bayesian Net. Results from experiments show that V-OWL has achieved good description of complex video content, and satisfactory precision and recall of high level semantic content detections.
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白亮,老松杨,刘海涛,等.基于OWL本体扩展的视频语义内容分析[J].国防科技大学学报,2010,32(2):79-84. BAI Liang, LAO Songyang, LIU Haitao, et al. Video Semantic Content Analysis Using Extensions to OWL[J]. Journal of National University of Defense Technology,2010,32(2):79-84.