基于格框架的视频事件时空相关描述分析方法

Spatio-temporal Correlation Described and Analysis Method of Video Event Based on Case Frame

在海量的视频资源中,如何描述和表示视频事件内容,是当下多媒体信息处理的热点问题之一。在用于自然语言理解的格语法理论基础上,引入了语义框架结构,设计了用以描述复杂事件中的子事件之间关系的格框架结构,并定义了视频综合事件中子事件框架关系。其中,在子事件参照关联关系上,对子事件的时间、空间关联性进行了分析推理。并采用格语义框架网络(Case Semantic Frame Net,CSFN)对实际监控视频集中的典型事件进行描述和时空关联分析,对比了格框架网络和传统格语法方法对事件进行描述分析之后,用户对视频进行检索的结果。实验证明,格框架网络能更加准确地描述和理解复杂事件,并有效提高视频事件检索的准确率和召回率。

In the mass of video resources, how to describe and represent video event content is one of hot issues in the current multimedia information processing. The original theory of case grammar for natural language understanding was extended; Case Frame was designed to describe the relationships between the structures of complex events in the sub-events. In Ref_Asso, which is one of relationships, spatio-temporal correlation was analyzed and reasoned among sub-events. In the experimental part, Case Semantic Frame Net was used to describe and understand the typical complex events in surveillance video. And results of users' retrieval were compared; in which video test set was described respectively with Case Semantic Frame Net and traditional Case grammar. Experiment results show that the new method can more accurately describe and understand complex events, and has a higher precision and recall rate in video retrieval.