基于变分光流的木质复合材料变形鲁棒估计
Robust Deformation Estimation in Wood-Composite Materials using Variational Optical Flow
摘要：
木材复合材料今天被广泛使用，因为它们均匀化与湿度相关的方向变形。将这些变形量化为系数对于建筑和工程以及当前研究的主题是重要的，但仍然是手动过程。这项工作介绍了一种新的计算机视觉的方法，自动提取这些属性直接从扫描的木材标本，在不同的湿度水平，在长期持久的湿度调节过程中。这些扫描用于计算每个像素的湿度相关变形场，从中可以容易地计算出所需的系数。整个方法包括自动注册的木块，数值优化计算的变化光流场，进一步用于计算密集的应变场，最后的工程系数和它们的方差在整个木块。该方法的正则化是完全参数化的，这允许建模和抑制工件由于表面外观的变化，从模具，裂纹等，通常出现在调节过程中的标本。
英文摘要：
Wood-composite materials are widely used today as they homogenize humidity related directional deformations. Quantification of these deformations as coefficients is important for construction and engineering and topic of current research but still a manual process. This work introduces a novel computer vision approach that automatically extracts these properties directly from scans of the wooden specimens, taken at different humidity levels during the long lasting humidity conditioning process. These scans are used to compute a humidity dependent deformation field for each pixel, from which the desired coefficients can easily be calculated. The overall method includes automated registration of the wooden blocks, numerical optimization to compute a variational optical flow field which is further used to calculate dense strain fields and finally the engineering coefficients and their variance throughout the wooden blocks. The methods regularization is fully parameterizable which allows to model and suppress artifacts due to surface appearance changes of the specimens from mold, cracks, etc. that typically arise in the conditioning process.
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