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Depth estimation and 3D reconstruction from UAV-borne imagery: Evaluation on the UseGeo dataset

Hermann, M. 1; Weinmann, M. 1; Nex, F.; Stathopoulou, E. K.; Remondino, F.; Jutzi, B. ORCID iD icon 1; Ruf, B. 1
1 Institut für Photogrammetrie und Fernerkundung (IPF), Karlsruher Institut für Technologie (KIT)

Abstract:

Depth estimation and 3D model reconstruction from aerial imagery is an important task in photogrammetry, remote sensing, and computer vision. To compare the performance of different image-based approaches, this study presents a benchmark for UAV-based aerial imagery using the UseGeo dataset. The contributions include the release of various evaluation routines on GitHub, as well as a comprehensive comparison of baseline approaches, such as methods for offline multi-view 3D reconstruction resulting in point clouds and triangle meshes, online multi-view depth estimation, as well as single-image depth estimation using self-supervised deep learning. With the release of our evaluation routines, we aim to provide a universal protocol for the evaluation of depth estimation and 3D reconstruction methods on the UseGeo dataset. The conducted experiments and analyses show that each method excels in a different category: the depth estimation from COLMAP outperforms that of the other approaches, ACMMP achieves the lowest error and highest completeness for point clouds, while OpenMVS produces triangle meshes with the lowest error. Among the online methods for depth estimation, the approach from the Plane-Sweep Library outperforms the FaSS-MVS approach, while the latter achieves the lowest processing time. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000171571
Veröffentlicht am 13.06.2024
Originalveröffentlichung
DOI: 10.1016/j.ophoto.2024.100065
Scopus
Zitationen: 2
Dimensions
Zitationen: 3
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Photogrammetrie und Fernerkundung (IPF)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 08.2024
Sprache Englisch
Identifikator ISSN: 2667-3932
KITopen-ID: 1000171571
Erschienen in ISPRS Open Journal of Photogrammetry and Remote Sensing
Verlag Elsevier
Band 13
Seiten Art.-Nr.: 100065
Vorab online veröffentlicht am 04.05.2024
Schlagwörter Depth estimation, 3D reconstruction, UAV, UseGeo, MVS, SMDE, NeRF
Nachgewiesen in Dimensions
Scopus
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