一种有效的视频场景检测方法

合理地组织视频数据对于基于内容的视频分析和应用有着重要的意义。现有的基于镜头的视频分析方法由于镜头信息粒度太小而不能反映视频语义上的联系，因此有必要将视频内容按照高层语义单元——场景进行组织。提出了一种快速有效的视频场景检测方法，根据电影编辑的原理，对视频场景内容的发展模式进行了分类，给出了场景构造的原则；提出一种新的基于滑动镜头窗的组合方法，将相似内容的镜头组织成为镜头类；定义了镜头类相关性函数来衡量镜头类之间的相关性并完成场景的生成。实验结果证明了该方法的快速有效性。

An Efficient Method for Video Scene Detection

It is important to organize the unstructured video data properly for content video analysis and application. However, existing shot-based video analysis can not get good performance for effective browsing and retrieval because shots are too numerous to handle and can not convey meaningful semantics, so it is necessary to organize video content with the scene structure, which is a more meaningful and high-level semantic video unit. In this paper, a simple and efficient method is presented for video scene detection. As the buildup of video scene should obey the film grammar, it concludes the types of the scenes that are widely used in filmmaking firstly. The rules to generating the video scene are put out then. Based on the rules, a scheme for video scene detection is proposed: The video stream is segmented into shots through shot boundary detection; Key frame extraction is performed based on the content variation of shots; A new clustering method based on the sliding shot window is used to group the shots into shot clusters; A correlation function between shot clusters is defined to analysis the correlations of them and to construct the final video scene structure. Experimental results verify it is an efficient method.