一种二级级联分类的镜头边界检测算法
Shot Boundary Detection Using a Cascade Classifier
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摘要: 在分析镜头边界类型、检测方法的基础上,根据镜头的连续性特征,将一个二级级联分类器应用于镜头边界检测.第一级分类器根据视频帧灰度方差特征,将无明显变化的视频序列从原始视频序列中分离出去,得到一个新的视频序列;第二级分类器在新视频序列的基础上,提取视频图像的像素对差值、HSV空间颜色直方图的各分量差值以及边缘直方图X,Y分量差值等视频特征,并采用支持向量机多分类策略进行镜头边界类型的检测.实验结果表明,与积聚算法及SVM-TMRA算法相比,文中算法的综合性能更高且具有较高的实时性.Abstract: Through the analysis of different kinds of shot boundaries,an algorithm for shot boundary detection based on a cascade classifier is proposed.The proposed algorithm first detects smooth intervals based on gray variance from the original frame sequence,then concatenates them to constructs a new frame sequence.After that,video features such as pixel-wise difference,HSV histogram difference and edge histogram difference are fed to a SVM classifier to decide the types of different shot boundaries.Experimental result shows that the proposed algorithm performs better than the accumulation and SVM-TMRA algorithm.
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