The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B2-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 519–526, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-519-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 519–526, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-519-2021

  28 Jun 2021

28 Jun 2021

INVESTIGATING 3D RECONSTRUCTION OF NON-COLLABORATIVE SURFACES THROUGH PHOTOGRAMMETRY AND PHOTOMETRIC STEREO

A. Karami1,2, F. Menna1, and F. Remondino1 A. Karami et al.
  • 13D Optical Metrology (3DOM) unit, Bruno Kessler Foundation (FBK), Trento, Italy
  • 2Dep. of Information Engineering and Computer Science, University of Trento, Trento, Italy

Keywords: Photogrammetry, Photometric stereo, Multiview Photometric stereo, industrial inspections

Abstract. 3D digital reconstruction techniques are extensively used for quality control purposes. Among them, photogrammetry and photometric stereo methods have been for a long time used with success in several application fields. However, generating highly-detailed and reliable micro-measurements of non-collaborative surfaces is still an open issue. In these cases, photogrammetry can provide accurate low-frequency 3D information, whereas it struggles to extract reliable high-frequency details. Conversely, photometric stereo can recover a very detailed surface topography, although global surface deformation is often present. In this paper, we present the preliminary results of an ongoing project aiming to combine photogrammetry and photometric stereo in a synergetic fusion of the two techniques. Particularly, hereafter, we introduce the main concept design behind an image acquisition system we developed to capture images from different positions and under different lighting conditions as required by photogrammetry and photometric stereo techniques. We show the benefit of such a combination through some experimental tests. The experiments showed that the proposed method recovers the surface topography at the same high-resolution achievable with photometric stereo while preserving the photogrammetric accuracy. Furthermore, we exploit light directionality and multiple light sources to improve the quality of dense image matching in poorly textured surfaces.