Measurement error with different computer vision techniques

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Abstract

The goal of this work is to offer a comparative of measurement error for different computer vision techniques for 3D reconstruction and allow a metrological discrimination based on our evaluation results. The present work implements four 3D reconstruction techniques: passive stereoscopy, active stereoscopy, shape from contour and fringe profilometry to find the measurement error and its uncertainty using different gauges. We measured several dimensional and geometric known standards. We compared the results for the techniques, average errors, standard deviations, and uncertainties obtaining a guide to identify the tolerances that each technique can achieve and choose the best.

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Icasio-Hernández, O., Curiel-Razo, Y. I., Almaraz-Cabral, C. C., Rojas-Ramirez, S. R., & González-Barbosa, J. J. (2017). Measurement error with different computer vision techniques. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives (Vol. 42, pp. 227–235). International Society for Photogrammetry and Remote Sensing. https://doi.org/10.5194/isprs-archives-XLII-2-W7-227-2017

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