A robust audio classification and segmentation method
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Shot clustering techniques for story browsing
IEEE Transactions on Multimedia
Scene extraction in motion pictures
IEEE Transactions on Circuits and Systems for Video Technology
Scene pathfinder: unsupervised clustering techniques for movie scenes extraction
Multimedia Tools and Applications
Hierarchical video summarization based on video structure and highlight
SSPR'06/SPR'06 Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Two important action scenes detection based on probability neural networks
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
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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.