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Moving Object Segmentation for Non-rigid-object by Bayesian Clustering

机译:贝叶斯聚类对非刚性物体的运动物体分割

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摘要

An algorithm for the segmentation of the non-rigid-object with accurate boundary using spatio-temporal information is proposed in this paper. The algorithm is composed of three parts: temporal segmentation, spatial segmentation, and region merging similar to a number of existing techniques. However, background register and an improved K-Means algorithm are used in the first and second part separately. After that, Bayesian clustering is used to merging the region. The experimental results of the proposed algorithm show the algorithm is efficient and accurate.
机译:提出了一种利用时空信息对边界准确的非刚性物体进行分割的算法。该算法由三部分组成:时间分割,空间分割和区域合并,类似于许多现有技术。但是,背景寄存器和改进的K-Means算法分别在第一部分和第二部分中使用。之后,将贝叶斯聚类用于合并区域。实验结果表明,该算法是有效且准确的。

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