Optimal Lateral Displacement in Automatic Close-Range Photogrammetry
Based on the use of automatic photogrammetry, different researchers made evident that the level of overlap between adjacent photographs directly affects the uncertainty of the 3D dense cloud originated by the Structure from Motion/Image Matching (SfM/IM) process. The purpose of this study was to inv...
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doaj-cd517d8ff0c04d698400ffad5a46f8a12020-11-25T04:05:08ZengMDPI AGSensors1424-82202020-11-01206280628010.3390/s20216280Optimal Lateral Displacement in Automatic Close-Range PhotogrammetryGabriele Guidi0Umair Shafqat Malik1Laura Loredana Micoli2Department of Mechanical Engineering, Politecnico di Milano, Via La Masa, 1, 20156 Milan, ItalyDepartment of Mechanical Engineering, Politecnico di Milano, Via La Masa, 1, 20156 Milan, ItalyDepartment of Mechanical Engineering, Politecnico di Milano, Via La Masa, 1, 20156 Milan, ItalyBased on the use of automatic photogrammetry, different researchers made evident that the level of overlap between adjacent photographs directly affects the uncertainty of the 3D dense cloud originated by the Structure from Motion/Image Matching (SfM/IM) process. The purpose of this study was to investigate if, in the case of a convergent shooting typical of close-range photogrammetry, an optimal lateral displacement of the camera for minimizing the 3D data uncertainty could be identified. We examined five different test objects made of rock, differing in terms of stone type and visual appearance. First, an accurate reference data set was generated by acquiring each object with an active range device, based on pattern projection (<i>σ<sub>z </sub></i>= 18 µm). Then, each object was 3D-captured with photogrammetry, using a set of images taken radially, with the camera pointing to the center of the specimen. The camera–object minimum distance was kept at 200 mm during the shooting, and the angular displacement was as small as π/60. We generated several dense clouds by sampling the original redundant sequence at angular displacements (<i>n</i>π/60, <i>n</i>=1, 2, … 8). Each 3D cloud was then compared with the reference, implementing an accurate scaling protocol to minimize systematic errors. The residual standard deviation of error made consistently evident a range of angular displacements among images that appear to be optimal for reducing the measurement uncertainty, independent of each specimen shape, material, and texture. Such a result provides guidance about how best to arrange the cameras’ geometry for 3D digitization of a stone cultural heritage artifact with several convergent shots. The photogrammetric tool used in the experiments was Agisoft Metashape.https://www.mdpi.com/1424-8220/20/21/6280photogrammetrycomputer visionSfM/IMimage overlap3D data uncertaintydistance/baseline ratio |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Gabriele Guidi Umair Shafqat Malik Laura Loredana Micoli |
spellingShingle |
Gabriele Guidi Umair Shafqat Malik Laura Loredana Micoli Optimal Lateral Displacement in Automatic Close-Range Photogrammetry Sensors photogrammetry computer vision SfM/IM image overlap 3D data uncertainty distance/baseline ratio |
author_facet |
Gabriele Guidi Umair Shafqat Malik Laura Loredana Micoli |
author_sort |
Gabriele Guidi |
title |
Optimal Lateral Displacement in Automatic Close-Range Photogrammetry |
title_short |
Optimal Lateral Displacement in Automatic Close-Range Photogrammetry |
title_full |
Optimal Lateral Displacement in Automatic Close-Range Photogrammetry |
title_fullStr |
Optimal Lateral Displacement in Automatic Close-Range Photogrammetry |
title_full_unstemmed |
Optimal Lateral Displacement in Automatic Close-Range Photogrammetry |
title_sort |
optimal lateral displacement in automatic close-range photogrammetry |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2020-11-01 |
description |
Based on the use of automatic photogrammetry, different researchers made evident that the level of overlap between adjacent photographs directly affects the uncertainty of the 3D dense cloud originated by the Structure from Motion/Image Matching (SfM/IM) process. The purpose of this study was to investigate if, in the case of a convergent shooting typical of close-range photogrammetry, an optimal lateral displacement of the camera for minimizing the 3D data uncertainty could be identified. We examined five different test objects made of rock, differing in terms of stone type and visual appearance. First, an accurate reference data set was generated by acquiring each object with an active range device, based on pattern projection (<i>σ<sub>z </sub></i>= 18 µm). Then, each object was 3D-captured with photogrammetry, using a set of images taken radially, with the camera pointing to the center of the specimen. The camera–object minimum distance was kept at 200 mm during the shooting, and the angular displacement was as small as π/60. We generated several dense clouds by sampling the original redundant sequence at angular displacements (<i>n</i>π/60, <i>n</i>=1, 2, … 8). Each 3D cloud was then compared with the reference, implementing an accurate scaling protocol to minimize systematic errors. The residual standard deviation of error made consistently evident a range of angular displacements among images that appear to be optimal for reducing the measurement uncertainty, independent of each specimen shape, material, and texture. Such a result provides guidance about how best to arrange the cameras’ geometry for 3D digitization of a stone cultural heritage artifact with several convergent shots. The photogrammetric tool used in the experiments was Agisoft Metashape. |
topic |
photogrammetry computer vision SfM/IM image overlap 3D data uncertainty distance/baseline ratio |
url |
https://www.mdpi.com/1424-8220/20/21/6280 |
work_keys_str_mv |
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