一种基于模型的扫换检测方法

视频自动分割是实现视频数据库检索必不可少的一个过程,其基础是镜头边界检测.当前已有的算法能够较准确地检测出镜头突变,但对于镜头的渐变则常常会漏检,这是由于镜头渐变时帧间差没有一个明显的峰值,因而其检测比突变检测要困难得多.扫换是一种常用的视频空间编辑手段,用于实现多种镜头变化.通过分析各种类型的扫换,提出了一种新的基于视频空间编辑模型的扫换检测算法,其性能优于Alattar提出的基于统计特征的算法.对用AdobePremiere5.1生成的各种扫换视频进行检测.实验结果表明,这种扫换检测算法能够较好地适应

A Model-Based Wipe Scene Change Detection Method

Automatic video segmentation, which is based on SBD (shot boundary detection), is one necessary step in establishing video databases. Existing SBD algorithms can detect abrupt scene changes quite accurately but may fail for gradual scene changes. This is due to the fact that there are no apparent peak values of frame difference during gradual scene change periods and hence it is more difficult to detect them. Wipes are frequently used to edit video in spatial domain to generate various kinds of scene changes. Through analysis of various wipes, a new algorithm is proposed in this paper based on a spatial editing model for wipe scene change detection. This method is better than the statistic-based method proposed by Alattar. Test results for video sequences generated by Adobe Premiere 5.1 containing wipe scene changes show that the algorithm is well suited for various types and durations of wipes.