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Soccer Video Shot Classification Based on Color Characterization Using Dominant Sets Clustering

机译:基于优势集聚类基于颜色特征的足球视频镜头分类

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摘要

In this paper, we propose a novel approach for dominant color region detection using dominant sets clustering and apply it to soccer video shot classification. Compared with the widely used histogram based dominant color extraction methods which require appropriate thresholds and sufficient training samples, the proposed method can automatically extract dominant color region without any threshold setting. Moreover, the dominant color distribution can be sufficiently characterized by the use of dominant sets clustering which naturally provides a principled measure of a cluster's cohesiveness as well as a measure of a vertex participation to each group. The Earth Mover's Distance (EMD) is employed to measure the similarity between dominant color regions of two frames, which is incorporated into the kernel function of SVM. Experimental results have shown the proposed method is much more effective.
机译:在本文中,我们提出了一种使用显性集聚类进行显色区域检测的新方法,并将其应用于足球视频镜头分类。与广泛使用的基于直方图的主色提取方法相比,该方法需要适当的阈值和足够的训练样本,该方法无需任何阈值设置即可自动提取主色区域。此外,可以通过使用优势集聚类来充分表征主导色分布,这自然提供了聚类的内聚性的原理性度量以及对每个组的顶点参与的度量。地球移动者的距离(EMD)用于测量两个帧的主色区域之间的相似度,并将其纳入SVM的内核功能中。实验结果表明,该方法更为有效。

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