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Enhancing motion segmentation by combination of complementary affinities

机译:通过补充亲和力来增强运动分割

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Complementary information, when combined in the right way, is capable of improving clustering and segmentation problems. In this paper, we show how it is possible to enhance motion segmentation accuracy with a very simple and inexpensive combination of complementary information, which comes from the column and row spaces of the same measurement matrix. We test our approach on the Hopkins155 dataset where it outperforms all other state-of-the-art methods.
机译:正确地组合了补充信息后,便可以改善聚类和分段问题。在本文中,我们展示了如何通过非常简单且便宜的补充信息组合(来自相同测量矩阵的列和行空间)来提高运动分割的准确性。我们在Hopkins155数据集上测试了我们的方法,该方法的性能优于所有其他最新方法。

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