Details
| Original language | English |
|---|---|
| Pages (from-to) | 299-315 |
| Number of pages | 17 |
| Journal | Photogrammetric Engineering and Remote Sensing |
| Volume | 86 |
| Issue number | 5 |
| Publication status | Published - 1 May 2020 |
Abstract
Recently, global structure from motion has successfully gained many followers, mainly because of its computational speed. Most of these global methods take the parameters of relative orientation (ROs) as input and then perform averaging operations. Therefore, eliminating incorrect ROs is of great significance for improving the robustness of global structure from motion. In this article, we propose a method to eliminate wrong ROs which have resulted from repetitive structure and very short baselines. We present two corresponding criteria that indicate the quality of ROs. Repetitive structure is detected based on counts of conjugate points of the various image pairs, while very short baselines are found by inspecting the intersection angles of corresponding image rays. By analyzing these two criteria, we detect and eliminate incorrect ROs. As correct ROs of image pairs with a longer baseline nearly parallel to both viewing direc-tions can be valuable, a method to identify and keep these ROs is also part of our approach. We demonstrate the new method on various data sets, including public benchmarksas well as close-range images and images from: unmanned Oaerial vehicles, by inserting ourr:refined ROs rinto a global fstructure-from-motion pipeline. The experiments show that compared to other methods, we can generate the best results.
ASJC Scopus subject areas
- Earth and Planetary Sciences(all)
- Computers in Earth Sciences
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In: Photogrammetric Engineering and Remote Sensing, Vol. 86, No. 5, 01.05.2020, p. 299-315.
Research output: Contribution to journal › Article › Research
}
TY - JOUR
T1 - An Improved Method of Refining Relative Orientation in Global Structure from Motion with a Focus on Repetitive Structure and Very Short Baselines
AU - Wang, X.
AU - Heipke, C.
N1 - Funding Information: Parts of this work were done at Vexcel Imaging, financially supported by the EU project VOLTA—innoVation in geOspatiaL and 3D daTA funded under the Marie-Curie RISE scheme as No. 734687. Xin Wang would like to thank the China Scholarship Council for financially supporting his PhD study at Leibniz Universität Hannover, Germany.
PY - 2020/5/1
Y1 - 2020/5/1
N2 - Recently, global structure from motion has successfully gained many followers, mainly because of its computational speed. Most of these global methods take the parameters of relative orientation (ROs) as input and then perform averaging operations. Therefore, eliminating incorrect ROs is of great significance for improving the robustness of global structure from motion. In this article, we propose a method to eliminate wrong ROs which have resulted from repetitive structure and very short baselines. We present two corresponding criteria that indicate the quality of ROs. Repetitive structure is detected based on counts of conjugate points of the various image pairs, while very short baselines are found by inspecting the intersection angles of corresponding image rays. By analyzing these two criteria, we detect and eliminate incorrect ROs. As correct ROs of image pairs with a longer baseline nearly parallel to both viewing direc-tions can be valuable, a method to identify and keep these ROs is also part of our approach. We demonstrate the new method on various data sets, including public benchmarksas well as close-range images and images from: unmanned Oaerial vehicles, by inserting ourr:refined ROs rinto a global fstructure-from-motion pipeline. The experiments show that compared to other methods, we can generate the best results.
AB - Recently, global structure from motion has successfully gained many followers, mainly because of its computational speed. Most of these global methods take the parameters of relative orientation (ROs) as input and then perform averaging operations. Therefore, eliminating incorrect ROs is of great significance for improving the robustness of global structure from motion. In this article, we propose a method to eliminate wrong ROs which have resulted from repetitive structure and very short baselines. We present two corresponding criteria that indicate the quality of ROs. Repetitive structure is detected based on counts of conjugate points of the various image pairs, while very short baselines are found by inspecting the intersection angles of corresponding image rays. By analyzing these two criteria, we detect and eliminate incorrect ROs. As correct ROs of image pairs with a longer baseline nearly parallel to both viewing direc-tions can be valuable, a method to identify and keep these ROs is also part of our approach. We demonstrate the new method on various data sets, including public benchmarksas well as close-range images and images from: unmanned Oaerial vehicles, by inserting ourr:refined ROs rinto a global fstructure-from-motion pipeline. The experiments show that compared to other methods, we can generate the best results.
UR - http://www.scopus.com/inward/record.url?scp=85100903476&partnerID=8YFLogxK
U2 - 10.14358/PERS.86.5.299
DO - 10.14358/PERS.86.5.299
M3 - Article
VL - 86
SP - 299
EP - 315
JO - Photogrammetric Engineering and Remote Sensing
JF - Photogrammetric Engineering and Remote Sensing
SN - 0099-1112
IS - 5
ER -