Straightforward reconstruction of 3D surfaces and topography with a camera: Accuracy and geoscience application

By Mike R. James, Stuart Robson. 2012

1,019 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition, Geology

View Paper: https://www.semanticscholar.org/paper/6cf4ac80cdf3d89c56ad2b29c22d9c7c5c6aba43

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In Aerospace Engineering

In Computer Vision and Pattern Recognition

In Geology

Citations in the corpus

Structure from motion photogrammetry in physical geography (2016, methodology): “fr/pmvs/) (Furukawa and Ponce, 2010) for dense cloud production is a common workflow (James and Robson, 2012).”
Spaceborne, UAV and ground-based remote sensing techniques for landslide mapping, monitoring and early warning (2017, methodology): “Furthermore, the recent development of new algorithms for digital photogrammetry, based on Structure from Motion (SfM) (Westoby et al. 2012) and Multi-View Stereo (MVS) (James and Robson, 2012) techniques, allows obtaining high-resolution 3D models, even by using compact and consumer-grade digital c”
Analyzing High Resolution Topography for Advancing the Understanding of Mass and Energy Transfer Through Landscapes: A Review (2015, methodology): “Recent photogrammetric techniques, such as Structure from Motion (SfM) (James and Robson, 2012) and Multi-View Stereo (MVS), can be mounted on UAVs and represent a low-cost option for acquiring HRT (Fig.”
Accuracy of Photogrammetric UAV-Based Point Clouds under Conditions of Partially-Open Forest Canopy (2017, background): “James and Robson [53] suggest that increasing the number of GCPs beyond the technical minimum provides a more robust solution less sensitive to errors on any point.”
Time Series Analysis of Landslide Dynamics Using an Unmanned Aerial Vehicle (UAV) (2015, methodology): “The mapping of three-dimensional terrain with SfM techniques has been demonstrated by authors such as Harwin and Lucieer [15], James and Robson [16], Ragg and Fey [17], Turner and Lucieer [18], Lucieer et al. [11], Lucieer et al. [19], and Westoby et al. [9].”
Evaluation of TanDEM-X DEMs on selected Brazilian sites: Comparison with SRTM, ASTER GDEM and ALOS AW3D30 (2017, methodology): “Maps of the differences between DEMs (here called DEMs of differences – DoDs) can be used to determine, for example, areas with changes in the land surface (James and Robson, 2012; Westoby et al., 2012; Clapuyt et al., 2016), map vegetation height (Carabajal and Harding, 2006; O’Loughlin et al.”
3D modelling of individual trees using a handheld camera: Accuracy of height, diameter and volume estimates (2015, methodology): “Structure-from-motion with multi-view stereo-photogrammetry (SfM-MVS) is a relatively new photogrammetric approach allowing automated reconstruction of 3D models using sets of overlapping 2D digital images (James and Robson, 2012).”
High Precision Individual Tree Diameter and Perimeter Estimation from Close-Range Photogrammetry (2018, methodology): “James and Robson [14] suggested a ratio of 1:1000 for the accuracy and distance; however, further testing is required.”
Optimal Altitude, Overlap, and Weather Conditions for Computer Vision UAV Estimates of Forest Structure (2015, methodology): “Similar processing pipelines that combine the Bundler source code with dense point cloud reconstruction techniques [47] have been used in other SFM remote sensing applications, including for 3D reconstruction of vineyards [26] and bare substrates [16,24,30–32,34].”
High-Resolution Airborne UAV Imagery to Assess Olive Tree Crown Parameters Using 3D Photo Reconstruction: Application in Breeding Trials (2015, methodology): “Yet, the emerging techniques of computer vision enable the generation of reliable 2D and 3D imagery from collections of multi-angle imagery acquired from standard (non-metric) cameras by using 3D photo-reconstruction algorithms based on structure-from-motion (SfM) and multi-view-stereo analysis algo”