Effective Video Scene Detection Approach Based on Cinematic Rules

Scene detection is an essential step to organize the video data properly for content-based video analysis and its application. In this paper, an effective scene detection approach is proposed, which exploits the cinematic rules used by filmmakers as guideline to compute shot similarities and identify the video scenes in narrative film. First, a clustering method with time constraint is used to group the shots into scene slices. Then dialog scene's alternative structure and audio correlation are used to identify dialog scene. Finally, motion and audio correlation guided by cinematic rules are used to further detect action scene. Experimental results show that the proposed method works well and can deal with complex scene.