基于OWL本体扩展的视频语义内容分析

Video Semantic Content Analysis Using Extensions to OWL

随着可获得视频数据的快速增长,迫切需要有效的方法在语义层理解和管理视频数据。对OWL语言进行扩展,提出了V-OWL本体描述框架,支持视频内容蕴含的时空关系和不确定性关系的建模,使用基于贝叶斯网络的B-图描述模型,将V-OWL本体概念、关系映射为B-图中的节点、边,利用贝叶斯网络训练推理算法实现视频高层语义的自动推理发现。实验结果显示,V-OWL本体描述框架对复杂视频内容具有很好的描述能力,基于V-OWL的视频内容分析框架对视频高层语义探测具有较高的查准率和查全率。

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 semantie 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 detectious.