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Dense Optical Flow Estimation from the Monogenic Curvature Tensor

机译:单峰曲率张量的密集光流估计

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摘要

In this paper, we address the topic of estimating two-frame dense optical flow from the monogenic curvature tensor. The monogenic curvature tensor is a novel image model, from which local phases of image structures can be obtained in a multi-scale way. We adapt the combined local and global (CLG) optical flow estimation approach to our framework. In this way, the intensity constraint equation is replaced by the local phase vector information. Optical flow estimation under the illumination change is investigated in detail. Experimental results demonstrate that our approach gives accurate estimation and is robust against noise contamination. Compared with the intensity based approach, the proposed method shows much better performance in estimating flow fields under brightness variations.
机译:在本文中,我们解决了从单基因曲率张量估计两帧密集光流的主题。单基因曲率张量是一种新颖的图像模型,从中可以以多尺度方式获得图像结构的局部相位。我们将组合的本地和全局(CLG)光流估算方法调整为适用于我们的框架。这样,强度约束方程被局部相位矢量信息代替。详细研究了光照变化下的光流估计。实验结果表明,我们的方法可以给出准确的估计值,并且对噪声污染具有鲁棒性。与基于强度的方法相比,该方法在估计亮度变化下的流场方面表现出更好的性能。

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