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A new content-based scene change detection method on compressed video

机译:一种基于内容的压缩视频场景变化检测新方法

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Scene change detection is the first step for automatic indexing of video data. In particular, it is desirable to detect scene changes on compressed data because this requires less processing overhead and storage to hold the results. Some approaches are proposed to detect scene changes on compressed data by computing the variances of DCT coefficients. However, these approaches do not consider the content in the image data, so undesirable results are often generated and no semantic information about the content is available. We propose a content-based scene change detection method by finding 3D connected volume from compressed video data. First, we find meaningful regions on the reduced DC image sequence using spatial coherence. Then, we compute correspondences of meaningful regions between successive frames using temporal coherence and finally detect scene changes by computing the change rate among meaningful regions along the time direction.
机译:场景变化检测是视频数据自动索引的第一步。特别地,期望检测压缩数据上的场景变化,因为这需要较少的处理开销和用于保存结果的存储。提出了一些方法,通过计算DCT系数的方差来检测压缩数据上的场景变化。但是,这些方法没有考虑图像数据中的内容,因此经常会产生不希望的结果,并且没有有关该内容的语义信息可用。我们提出了一种基于内容的场景变化检测方法,该方法通过从压缩视频数据中找到3D连接体积来进行。首先,我们使用空间相干性在缩小的DC图像序列上找到有意义的区域。然后,我们使用时间相干性计算连续帧之间有意义区域的对应关系,并通过计算沿时间方向有意义区域之间的变化率来最终检测场景变化。

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