一种分层的和多分辨的镜头边界检测方法

A Hierarchical and Multiresolution Detection Method of Shot Transition for Video Shots Segmentation

提出了一种分层的和多分辨的镜头边界检测方法。该方法对各种不同的镜头间过渡类型给出了用不同方法进行联合检测的方案,该方案主要分为突变镜头检测(即视频切分)、淡化过渡检测、溶解过渡检测及划变过渡检测4个部分。检测方案并不是简单地将各种方法拼接在一起,而是通过小波变换的多分辨分析将它们有机地结合起来,相互关联,达到有效检测结果。首先用FCM聚类算法进行视频切分,然后根据聚类结果分别在整数小波分解后的高频部分用Gaussian加权Hausdorff距离结合边界改变率算法检测淡化过渡;对分解后的低频部分用所提出的SCD算法(Similarity of color distribution based method)检测溶解过渡,并通过自适应调节权系数(系数盲调节)使检测相异度函数更能适用于多种视频片段。最后根据切分以及前面两种过渡检测的结果,利用三维小波分解后高频成分中的运动部分所定义的运动矢量来检测划变过渡。用实际视频数据所做的仿真实验结果表明,该方法不但能同时检测突变过渡和渐变过渡,而且能准确地判断渐变过渡的类型及其位置。此外,还能有效地抑制闪光、运动等的影响,从而提高了检测精度。

According to the drawbacks of available algorithms, a new hierarchical and multiresolution approach to the detection and classification of scene breaks in video sequences is presented in this paper. This method gives the detecT tion scheme for different shots using different algorithms. This scheme includes four parts, cut detection（video cut）, fade detection, dissolve detection and wipe detection. Firstly, the video clips are cut by FCM clustering method, then the fade and dissolve are detected using Hausdorff distance and SCD algorithm in the high components and the low com- ponents respectively by integer-to-integer wavelet transform. Finally, according to the cut and the former detection of gradual changes, we use a motion vector in high-components of 3D-WT to detect the wipe transition. Experimental re sults with real video clips demonstrate that our method can detect and classify a variety of scene breaks, including cuts, fades and dissolves, even in sequences involving significant motions and flash.