This paper proposes a method of abrupt cut detection based on motion information. Quantitative angle histogram entropy and average magnitude are defined to be the metrics of frame differences from the motion vector filed calculated by block-based motion estimation. Adaptive threshold strategies are designed to identify candidate abrupt cuts. False cuts caused by flashes and gradual transitions are eliminated by using a temporal window. In the process of key frame extraction, different algorithms which have different limitations of the number of extraction are selected adaptively according to the extents of similarity of video frames content. Experimental results show that the method has high accuracy and robustness.%提出一种基于运动信息的镜头切变检测方法.在运动估计得到的运动矢量场中定义角度直方图熵和幅度2个运动特征,作为视频帧间差异度量的标准.设计自适应阈值策略,得到候选切变点,针对摄像机闪光和旋转变焦带来的干扰,设计时域窗策略,剔除虚假切点.在提取关键帧时,根据镜头内的视频帧间差异程度,自适应地选取具有不同提取帧数上限的算法.实验结果表明,该方法具有准确性高和鲁棒性强的特点.
展开▼
