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Streaming Graph-Based Hierarchical Video Segmentation by a Simple Label Propagation

机译:通过简单的标签传播流媒体基于图形的分层视频分段

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In this paper, we present an approach to streaming graph-based hierarchical video segmentation by simple label propagation. Here, we transform the streaming video segmentation into a graph partitioning problem in which each part corresponds to one region of the video, furthermore, we apply a simple method for merging the segmentations of two consecutive blocks to achieve the temporal coherence. The spatial-temporal coherence is given, only, by color information instead of more complex features. We provide an extensive comparative analysis among our method and methods in the literature showing efficiency, ease of use, and temporal coherence of ours. According to the experiments, our method produces good results when applied to video segmentation besides presenting a low space and time cost, compared to other methods.
机译:在本文中,我们通过简单的标签传播介绍了一种基于图形的分层视频分段的方法。这里,我们将流媒体视频分段转换为曲线图分区问题,其中每个部分对应于视频的一个区域,此外,我们应用了一种简单的方法,用于合并两个连续块的分割以实现时间相干性。仅通过颜色信息而不是更复杂的功能给出空间 - 时间相干性。我们在文献中提供了广泛的比较分析,在文献中显示了显示效率,易用性和我们的时间相干性。根据实验,除了呈现低空间和时间成本之外,我们的方法在应用于视频分割时产生良好的结果,与其他方法相比。

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