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Robust Shape and Polarisation Estimation Using Blind Source Separation

机译:使用盲源分离的稳健形状和偏振估计

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In this paper we show how to use blind source separation to estimate shape from polarised images. We propose a new method which does not require prior knowledge of the polariser angles. The two key ideas underpinning the approach are to use weighted Singular Value De-composition(SVD) to estimate the polariser angles, and to use a mutual information criterion function to optimise the weights. We calculate the surface normal information using Presnel equation, and iteratively update the values of weighting matrix and refractive index to a recover surface shape. We show that the proposed method is capable of calculating robust shape information compared with alternative approaches based on the same inputs. Moreover, the method can be applied when using uncalibrated polarisation filters. This is the case when the the subject is difficult to stabilse during image capture.
机译:在本文中,我们展示了如何使用盲源分离来估计偏振图像的形状。我们提出了一种不需要偏振器角度的先验知识的新方法。支持该方法的两个关键思想是使用加权奇异值分解(SVD)来估计偏振器角度,并使用互信息准则函数来优化权重。我们使用Presnel方程计算表面法线信息,然后将权重矩阵和折射率的值迭代更新为恢复的表面形状。我们表明,与基于相同输入的替代方法相比,所提出的方法能够计算鲁棒的形状信息。而且,当使用未校准的偏振滤波器时,可以应用该方法。当对象在图像捕获期间难以稳定时,就是这种情况。

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