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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基于图的分层视频分割

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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,我们提出了一种通过简单的标签传播流化基于图的分层视频分割的方法。在这里,我们将流视频分割转换为图分割问题,其中每个部分对应于一个视频区域,此外,我们应用一种简单的方法来合并两个连续块的分割,以实现时间一致性。时空连贯性仅通过颜色信息而不是更复杂的特征给出。我们在文献中对我们的方法进行了广泛的比较分析,显示了我们的方法的效率,易用性和时间一致性。根据实验,与其他方法相比,该方法在应用于视频分割时除具有较低的空间和时间成本外,还产生了良好的效果。

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