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Video segmentation based on 2D image analysis

机译:基于2D图像分析的视频分割

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The video segmentation problem consists in the identification of the boundary between consecutive shots. The common approach to solve this problem is based on dissimilarity measures between frames. In this work, the video segmentation problem is transformed into a problem of pattern detection, where each video event is transformed into a different pattern on a 2D image, called visual rhythm, obtained by a specific transformation. In our analysis we use topological and morphological tools to detect cuts. Also, we use discrete line analysis and max tree analysis to detect fade transitions and flashes, respectively. We present a comparative analysis of our method for cut detection with respect to some other methods, which shows the better results of our method.
机译:视频分割问题在于识别连续镜头之间的边界。解决此问题的常用方法是基于帧之间的差异度量。在这项工作中,视频分割问题被转换为模式检测问题,其中每个视频事件在2D图像上被转换为通过特定转换获得的称为视觉节奏的不同模式。在我们的分析中,我们使用拓扑和形态学工具来检测切割。此外,我们分别使用离散线分析和最大树分析来检测淡入过渡和闪烁。我们介绍了我们的割痕检测方法相对于其他方法的比较分析,显示了我们方法的更好结果。

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