Details
| Original language | English |
|---|---|
| Pages (from-to) | 295-302 |
| Number of pages | 8 |
| Journal | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Volume | 4 |
| Issue number | 2 |
| Publication status | Published - 28 May 2018 |
| Event | 2018 ISPRS TC II Mid-term Symposium "Towards Photogrammetry 2020" - Riva del Garda, Italy Duration: 4 Jun 2018 → 7 Jun 2018 |
Abstract
In this paper we present a novel approach for image orientation by combining relative rotations and tie points. First, we choose an initial image pair with enough correspondences and large triangulation angle, and we then iteratively add clusters of new images. The rotation of these newly added images is estimated from relative rotations by single rotation averaging. In the next step, a linear equation system is set up for each new image to solve the translation parameters with triangulated tie points which can be viewed in that new image, followed by a resection for refinement. Finally, we optimize the cluster of reconstructed images by local bundle adjustment. We show results of our approach on different benchmark datasets. Furthermore, we orient several larger datasets incl. unordered image datasets to demonstrate the robustness and performance of our approach.
Keywords
- image orientation, single rotation averaging, structure from motion (SfM), translation estimation
ASJC Scopus subject areas
- Earth and Planetary Sciences(all)
- Earth and Planetary Sciences (miscellaneous)
- Environmental Science(all)
- Environmental Science (miscellaneous)
- Physics and Astronomy(all)
- Instrumentation
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In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 4, No. 2, 28.05.2018, p. 295-302.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Robust image orientation based on relative rotations and tie points
AU - Wang, X.
AU - Rottensteiner, F.
AU - Heipke, C.
N1 - Funding Information: The author Xin Wang would like to thank the China Scholarship Council (CSC) for financially supporting his PhD study at Leibniz Universität Hannover, Germany.
PY - 2018/5/28
Y1 - 2018/5/28
N2 - In this paper we present a novel approach for image orientation by combining relative rotations and tie points. First, we choose an initial image pair with enough correspondences and large triangulation angle, and we then iteratively add clusters of new images. The rotation of these newly added images is estimated from relative rotations by single rotation averaging. In the next step, a linear equation system is set up for each new image to solve the translation parameters with triangulated tie points which can be viewed in that new image, followed by a resection for refinement. Finally, we optimize the cluster of reconstructed images by local bundle adjustment. We show results of our approach on different benchmark datasets. Furthermore, we orient several larger datasets incl. unordered image datasets to demonstrate the robustness and performance of our approach.
AB - In this paper we present a novel approach for image orientation by combining relative rotations and tie points. First, we choose an initial image pair with enough correspondences and large triangulation angle, and we then iteratively add clusters of new images. The rotation of these newly added images is estimated from relative rotations by single rotation averaging. In the next step, a linear equation system is set up for each new image to solve the translation parameters with triangulated tie points which can be viewed in that new image, followed by a resection for refinement. Finally, we optimize the cluster of reconstructed images by local bundle adjustment. We show results of our approach on different benchmark datasets. Furthermore, we orient several larger datasets incl. unordered image datasets to demonstrate the robustness and performance of our approach.
KW - image orientation
KW - single rotation averaging
KW - structure from motion (SfM)
KW - translation estimation
UR - http://www.scopus.com/inward/record.url?scp=85048403458&partnerID=8YFLogxK
U2 - 10.5194/isprs-annals-IV-2-295-2018
DO - 10.5194/isprs-annals-IV-2-295-2018
M3 - Conference article
AN - SCOPUS:85048403458
VL - 4
SP - 295
EP - 302
JO - ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
JF - ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
SN - 2194-9042
IS - 2
T2 - 2018 ISPRS TC II Mid-term Symposium "Towards Photogrammetry 2020"
Y2 - 4 June 2018 through 7 June 2018
ER -