摘要
为了有效地进行视频镜头边界检测,在简要介绍了现有的镜头边界检测基本方法的基础上提出了基于SVD的镜头边界检测方法。该方法通过特征提取来构造视频特征矩阵,经过SVD变换得到特征值矩阵,然后将特征值矩阵映射到向量空间,最后通过分析向量间的夹角来判断镜头的变化。实验结果表明,在镜头边界检测性能上优于已有的基于帧差的双阈值镜头边界检测方法。
The fundamental methods for shot boundary detection were briefly introduced at the beginning, and then a new method based on Singular Value Decomposition (SVD) was proposed. First, construct the video feature matrix and get the eigenvalue matrix through the transform of SVD. Second, map the elgenvalue matrix into vector space. Finally, detect the shot change by the angle of vectors. Experimental results demonstrate the method is superior to the frame-difference based double threshold shot boundary detection.
出处
《计算机应用》
CSCD
北大核心
2007年第1期155-156,159,共3页
journal of Computer Applications
基金
国家自然科学基金资助项目(60572080)
关键词
镜头边界检测
奇异值分解
视频特征提取
视频特征矩阵
shot boundary detection, SVD( Singular Value Decomposition), video feature extraction, video feature matrix