Spectral grouping using the Nystrom method
Spectral grouping using the Nystrom method
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DOI：
10.1109/tpami.2004.1262185
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发表时间：
2004-02-01
影响因子：
23.6
通讯作者：
Malik, J
中科院分区：
文献类型：
--
作者：
Fowlkes, C;Belongie, S;Malik, J
近年来，光谱图理论方法在图像分割问题上显示出很大的前景。然而，由于这些方法的计算需求，在诸如时空数据和高分辨率图像等大型问题上的应用一直缓慢出现。本文的贡献在于提供了一种方法，该方法大大降低了基于谱划分的分组算法的计算需求，使其能够应用于非常大的分组问题。我们的方法是基于一种被称为Nystrom方法的特征函数问题数值解的技术。这种方法允许人们仅使用少量样本就可以推断出完整的分组解决方案。在这样做的过程中，我们利用了一个事实，即在一个场景中有比像素少得多的连贯组。
Spectral graph theoretic methods have recently shown great promise for the problem of image segmentation. However, due to the computational demands of these approaches, applications to large problems such as spatiotemporal data and high resolution imagery have been slow to appear. The contribution of this paper is a method that substantially reduces the computational requirements of grouping algorithms based on spectral partitioning making it feasible to apply them to very large grouping problems. Our approach is based on a technique for the numerical solution of eigenfunction problems known as the Nystrom method. This method allows one to extrapolate the complete grouping solution using only a small number of samples. In doing so, we leverage the fact that there are far fewer coherent groups in a scene than pixels.