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Peekaboo-Where are the Objects? Structure Adjusting Superpixels

机译:Peekaboo - 物体在哪里?结构调整超像素

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This paper addresses the search for a fast and meaningful image segmentation in the context of k-means clustering. The proposed method builds on a widely-used local version of Lloyd's algorithm, called Simple Linear Iterative Clustering (SLIC). We propose an algorithm which extends SLIC to dynamically adjust the local search, adopting superpixel resolution dynamically to structure existent in the image, and thus provides for more meaningful superpixels in the same linear runtime as standard SLIC. The proposed method is evaluated against state-of-the-art techniques and improved boundary adherence and undersegmentation error are observed, whilst still remaining among the fastest algorithms which are tested.
机译:本文在K-Means群集的上下文中寻找快速和有意义的图像分段。所提出的方法在LLOYD算法的广泛使用本地版本上构建,称为简单的线性迭代聚类(SLIC)。我们提出了一种算法,它延伸了SLIC以动态调整本地搜索,采用Superpixel分辨率动态地与图像中存在的结构,从而为与标准SLIC相同的线性运行时提供更有意义的超像素。该提出的方法是针对最先进的技术评估的,并且观察到改进的边界依从性和缺记误差,同时仍留在测试的最快算法中。

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