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The project aims to improve automated 3D reconstruction methods via vision metrology solutions. This research strives to demonstrate a step towards narrowing the gap between traditional Vision Metrology (VM) approaches and fully automated 3D reconstruction methods. Efforts are therefore intended to (i) test the metric performance of the automated photogrammetric 3D reconstruction procedure, (ii) enhance the accuracy of the final results and (iii) obtain statistical indicators of the quality achieved in the orientation step. VM tools are exploited to integrate their main functionalities (centroid measurement, photogrammetric network adjustment, precision assessment, etc.) into the pipeline of 3D dense reconstruction. Finally, geometric analyses and accuracy evaluations are performed on the raw output of the matching (i.e. the point clouds) by adopting a metrological approach. (e.g. following VDI/VDE guidelines).
- MacDonald, L., Toschi, I., Nocerino, E., Hess, M., Remondino, F. and Robson, S., 2016: Accuracy of 3D Reconstruction in an Illumination Dome. ISPRS Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XLI-B5, pp. 69-76
- Toschi, I., Nocerino, Hess, M., Menna, F., Sargeant, B., MacDonald, L.W., Remondino, F., Robson, S., 2015: Improving automated 3D reconstruction methods via vision metrology. Proc. of Videometrics, Range Imaging and Applications XIII, SPIE Optical Metrology, Vol. 9528
UCL - Department of Civil, Environmental and Geomatic Engineering (CEGE) & 3DIMPACT group.