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Title: Automated Aerial Triangulation for UAV-Based Mapping

Journal Article · · Remote Sensing
DOI:https://doi.org/10.3390/rs10121952· OSTI ID:1613657
ORCiD logo [1];  [1];  [1];  [1];  [1]
  1. Purdue Univ., West Lafayette, IN (United States)
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Accurate 3D reconstruction/modelling from unmanned aerial vehicle (UAV)-based imagery has become the key prerequisite in various applications. Although current commercial software has automated the process of image-based reconstruction, a transparent system, which can be incorporated with different user-defined constraints, is still preferred by the photogrammetric research community. In this regard, this paper presents a transparent framework for the automated aerial triangulation of UAV images. The proposed framework is conducted in three steps. In the first step, two approaches, which take advantage of prior information regarding the flight trajectory, are implemented for reliable relative orientation recovery. Then, initial recovery of image exterior orientation parameters (EOPs) is achieved through either an incremental or global approach. Finally, a global bundle adjustment involving Ground Control Points (GCPs) and check points is carried out to refine all estimated parameters in the defined mapping coordinate system. Four real image datasets, which are acquired by two different UAV platforms, have been utilized to evaluate the feasibility of the proposed framework. In addition, a comparative analysis between the proposed framework and the existing commercial software is performed. The derived experimental results demonstrate the superior performance of the proposed framework in providing an accurate 3D model, especially when dealing with acquired UAV images containing repetitive pattern and significant image distortions.

Research Organization:
Purdue Univ., West Lafayette, IN (United States)
Sponsoring Organization:
USDOE Advanced Research Projects Agency - Energy (ARPA-E)
Grant/Contract Number:
AR0000593
OSTI ID:
1613657
Journal Information:
Remote Sensing, Vol. 10, Issue 12; ISSN 2072-4292
Publisher:
MDPICopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 36 works
Citation information provided by
Web of Science

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Cited By (6)

UAV RTK/PPK Method—An Optimal Solution for Mapping Inaccessible Forested Areas? journal March 2019
Topology-Aware Road Network Extraction via Multi-Supervised Generative Adversarial Networks journal April 2019
Three-Dimensional Reconstruction of Structural Surface Model of Heritage Bridges Using UAV-Based Photogrammetric Point Clouds journal May 2019
Evaluation of UAV LiDAR for Mapping Coastal Environments journal December 2019
Towards Benthic Habitat 3D Mapping Using Machine Learning Algorithms and Structures from Motion Photogrammetry journal January 2020
GNSS/INS-Assisted Structure from Motion Strategies for UAV-Based Imagery over Mechanized Agricultural Fields journal January 2020

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47 OTHER INSTRUMENTATION
Remote Sensing
unmanned aerial vehicle
3D reconstruction
structure from motion
relative orientation
exterior orientation parameters
bundle adjustment