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Improvement of shot detection using illumination invariant metric and dynamic threshold selection

机译:使用光照不变度量和动态阈值选择改进镜头检测

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Automatic shot detection is the first step and also an important step for content-based parsing and indexing of video data.Many methods have been introduced to address this problem.e.g.pixel-by-pixel comparisons and histogram comparisons.But gray or color histograms used in most existing methods ignore hte problem of illumination variation inherent in the video production process.So they often fail when the incident illumination varies.And because shot change is basically a local process of a video,it is difficult to find an appropriate global threshold for absolute difference measure.In this paper,new techniques for shot detection are proposed.We use color ratio histograms as frame content measure,because it is robust to illumination changes.A local adaptive threshold technique is adopted to utilize the local characteristic of shot change.The effectiveness of our methods is validated by experiments on some real-world video sequences.Some experimental results are also discussed in this paper.
机译:自动镜头检测是基于内容的视频数据解析和索引的第一步,也是重要的一步,已经引入了许多方法来解决此问题,例如逐像素比较和直方图比较,但是使用了灰度或彩色直方图在大多数现有方法中,都忽略了视频制作过程中固有的照明变化问题。因此,当入射照明变化时,它们通常会失败。而且由于镜头变化基本上是视频的局部过程,因此很难找到合适的全局阈值本文提出了一种用于镜头检测的新技术。我们采用色彩比直方图作为帧内容度量,因为它对光照变化具有鲁棒性。采用局部自适应阈值技术来利用镜头变化的局部特征。通过在一些真实视频序列上的实验验证了我们方法的有效性。本实验还讨论了一些实验结果纸。

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