摘要
提出了一种高效的视频场景检测方法。首先基于均值漂移,在滑动镜头窗内对各镜头聚类,并获得相应的聚类中心,然后根据电影视频场景的发展模式,计算两个镜头类之间的时序距离,接着基于时空关系进行场景检测,并且由相应的聚类中心获得场景关键帧,最后对场景过分割进行后续处理。实验证实该方法能快速聚类,并且有效地检测出场景和场景关键帧。
An efficient algorithm for scene detection is proposed. Where firstly within a sliding shot window, the shots are clustered and each cluster center is achieved rapidly by employing MS clustering, then according to the development pattern of film video scene, the temporal distances between two shots are computed and scenes are detected based on the temporal and spatial relationship. In addition, the scene key frames can be achieved on the basis of corresponding cluster centers. Finally, a succeeding procession for over-segmented scenes is introduced. Experiments prove this algorithm can cluster shots rapidly and detect scenes and the key frames of the scence efficiently.
出处
《中国图象图形学报》
CSCD
北大核心
2010年第2期314-320,共7页
Journal of Image and Graphics
基金
南京理工大学科技发展基金(XKF09023)
关键词
均值漂移
聚类
镜头类
场景检测
场景关键帧
mean shift, clustering, shot cluster, scene detection, scene key frame
