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Automatic Segmentation of Non-rigid Objects in Image Sequences Using Spatiotemporal Information

机译:使用时空信息自动分割图像序列中的非刚性物体

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This paper provides an automatic segmentation method of non-rigid objects in image sequences. The non-rigid objects have fuzzy, blurred, and indefinite boundaries such as smoke and clouds, and are random and unpredictable in spatial and temporal domains. To segment the non-rigid objects, a new segmentation approach considering random and unpredictable characteristics of the non-rigid objects is needed. In this paper, we propose a new segmentation method of the non-rigid objects in image sequences using spatiotemporal information. The procedure toward complete segmentation consists of three steps: spatial segmentation, temporal segmentation, and fusion of the spatial and temporal segmentation results. By means of experiments on various test sequences, we demonstrate that the performance of our method is quite impressive from the viewpoints of the segmentation accuracy.
机译:本文提供了一种图像序列中的非刚性物体的自动分段方法。非刚性物体具有模糊,模糊和无限的边界,例如烟雾和云,并且在空间和时间域中是随机和不可预测的。为了分割非刚性物体,需要考虑非刚性物体的随机和不可预测的特征的新分割方法。本文使用时空信息提出了一种新的图像序列中的非刚性物体的新分割方法。完整分割的程序包括三个步骤:空间分割,时间分割和空间和时间分割结果的融合。通过对各种测试序列的实验,我们证明我们的方法的性能从分割精度的观点来看是非常令人印象深刻的。

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