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We present a novel algorithm explicitly tailored to estimate motion from timeseries of 3D images of concrete. Such volumetric images are usually acquired byComputed Tomography and can contain for example in situ tests, or more complexprocedures like self-healing. Our algorithm is specifically designed to tacklethe challenge of large scale in situ investigations of concrete. That means itcannot only cope with big images, but also with discontinuous displacementfields that often occur in in situ tests of concrete. We show the superiorperformance of our algorithm, especially regarding plausibility and timeefficient processing. Core of the algorithm is a novel multiscalerepresentation based on morphological wavelets. We use two examples forvalidation: A classical in situ test on refractory concrete and and a threepoint bending test on normal concrete. We show that for both applicationsstructural changes like crack initiation can be already found at low scales --a central achievement of our algorithm.

MorphFlow: Estimating Motion in In Situ Tests of Concrete