Audio PCA in a novel multimedia scheme for scene change detection

A novel scene change detection algorithm is proposed in this paper that exploits both audio and video information. Audio frames are projected to the eigenspace and their distance from a reference noise eigenframe is calculated. An analysis is presented that explains why this subspace favors scene cut detection. Video information is used to align audio scene change indications with neighboring shot changes in the visual data, and accordingly to reduce the false alarm rate. Moreover, video fade effects are identified and used independently in order to track scene changes. The detection technique was tested on newscast videos provided by the TRECVID 2003 video test set. The experimental results show that the aforementioned methods used to process the audio and video information complement each other well in tackling the scene change detection problem.