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

机译:压缩视频中基于新的基于内容的场景改变检测方法

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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:场景变更检测是自动索引视频数据的第一步。特别地,希望检测压缩数据的场景改变,因为这需要较少的处理开销和存储来保持结果。提出了一些方法来通过计算DCT系数的差异来检测压缩数据的场景变化。然而,这些方法不考虑图像数据中的内容,因此通常生成不期望的结果,并且没有有关内容的语义信息可用。我们通过查找来自压缩视频数据的3D连接的音量提出基于内容的场景改变检测方法。首先,我们使用空间相干性地在减少的直流图像序列上找到有意义的区域。然后,我们使用时间相干性地计算连续帧之间的有意义区域的对应关系,并且通过沿着时间方向计算有意义的区域之间的变化率来检测场景改变。

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