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Wood-composite materials are widely used today as they homogenize humidityrelated directional deformations. Quantification of these deformations ascoefficients is important for construction and engineering and topic of currentresearch but still a manual process.  This work introduces a novel computer vision approach that automaticallyextracts these properties directly from scans of the wooden specimens, taken atdifferent humidity levels during the long lasting humidity conditioningprocess. These scans are used to compute a humidity dependent deformation fieldfor 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 isfurther used to calculate dense strain fields and finally the engineeringcoefficients and their variance throughout the wooden blocks. The methodsregularization is fully parameterizable which allows to model and suppressartifacts due to surface appearance changes of the specimens from mold, cracks,etc. that typically arise in the conditioning process.

Robust Deformation Estimation in Wood-Composite Materials using Variational Optical Flow