A two-step approach for the correction of rolling shutter distortion in UAV photogrammetry

Zhou, Yinghui; Daakir, M.; Rupnik, Ewelina; Pierrot-Deseilligny, Marc

doi:10.1016/j.isprsjprs.2019.11.020

Cited by 32 publications

(29 citation statements)

References 18 publications

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“…Analysis of the final errors in specific variants shows that these variants are close to each other despite the use of cameras which are equipped with different shutters. Control of the direct effect of the rolling shutter modelling function allows the observation that, when this option is not used in the adjustment, the model is characterised with a significantly larger error rate (Wiącek and Pyka, 2019; Zhou et al., 2020). Similar analyses were performed for the photographs of the global shutter camera and no clear differences were found between the results obtained with and without the rolling shutter modelling option.…”

Section: Discussionmentioning

confidence: 99%

“…With reference to point (a), one of the most significant elements of the camera, which undoubtedly affects the image geometry, is the shutter speed (the length of time the camera’s shutter is open (Vautherin et al., 2016; Ito and Okatani, 2017; Granshaw, 2020; Zhou et al., 2020)). There are two categories of shutter: global shutters and rolling shutters.…”

Section: Introductionmentioning

confidence: 99%

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Determining optimal photogrammetric adjustment of images obtained from a fixed‐wing UAV

Pargieła

Rzonca

2021

The Photogrammetric Record

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Photogrammetry with unmanned aerial vehicles (UAVs) has become a source of data with extensive applications. The accuracy is of utmost significance, yet the intention is also to find the best possible solutions for data acquisition in economic terms. The objective of the research was the analysis of various variants of the bundle block adjustment. The analysis concerns data which is diversified with respect to the type of shutter (rolling/global), the measurement of external orientation elements, the overlap and the number of ground control points (GCPs).

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Determining optimal photogrammetric adjustment of images obtained from a fixed‐wing UAV

Pargieła

Rzonca

2021

The Photogrammetric Record

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“…The modeling software used for rendering SfM models in this case study is Agisoft Metashape 1.5.5 [53]. Agisoft Metashape (previously, Agisoft Photoscan https://www.agisoft.com/) is widely used by the photogrammetry research community [54,55]. Additionally, CloudCompare (http://www.…”

Section: Selection Of Equipment and Modeling Softwarementioning

confidence: 99%

Automated 3D Reconstruction Using Optimized View-Planning Algorithms for Iterative Development of Structure-from-Motion Models

et al. 2020

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Unsupervised machine learning algorithms (clustering, genetic, and principal component analysis) automate Unmanned Aerial Vehicle (UAV) missions as well as the creation and refinement of iterative 3D photogrammetric models with a next best view (NBV) approach. The novel approach uses Structure-from-Motion (SfM) to achieve convergence to a specified orthomosaic resolution by identifying edges in the point cloud and planning cameras that “view” the holes identified by edges without requiring an initial model. This iterative UAV photogrammetric method successfully runs in various Microsoft AirSim environments. Simulated ground sampling distance (GSD) of models reaches as low as 3.4 cm per pixel, and generally, successive iterations improve resolution. Besides analogous application in simulated environments, a field study of a retired municipal water tank illustrates the practical application and advantages of automated UAV iterative inspection of infrastructure using 63 % fewer photographs than a comparable manual flight with analogous density point clouds obtaining a GSD of less than 3 cm per pixel. Each iteration qualitatively increases resolution according to a logarithmic regression, reduces holes in models, and adds details to model edges.

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“…Figure 10 shows an object moving in the angular direction of ω on the image plane. By the law of sines, the length of 2 ̅̅̅̅̅ can be derived by Equation (12).…”

Section: Derivation Of the Rse Equation: The Movement Of The Object Has A Certain Angle To The Image Planementioning

confidence: 99%

“…Kim et al [10] applied the rolling shutter concept to simultaneous localization and mapping (SLAM) photogrammetry and Vautherin et al [11] to UAV photogrammetry to improve the three-dimensional positional accuracy. Zhou et al [12] performed mathematical modeling of the sensor's readout time to eliminate distortion caused by the rolling shutter and performed bundle block adjustment. The discussions have been made on the relative pose estimation [13] and absolute pose estimation [14,15] of the rolling shutter cameras.…”

Section: Introductionmentioning

confidence: 99%

Object Distance Estimation Using a Single Image Taken from a Moving Rolling Shutter Camera

Kim

Bae

Kim

et al. 2020

Sensors

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This paper proposes a technique to estimate the distance between an object and a rolling shutter camera using a single image. The implementation of this technique uses the principle of the rolling shutter effect (RSE), a distortion within the rolling-shutter-type camera. The proposed technique has a mathematical strength compared to other single photo-based distance estimation methods that do not consider the geometric arrangement. The relationship between the distance and RSE angle was derived using the camera parameters (focal length, shutter speed, image size, etc.). Mathematical equations were derived for three different scenarios. The mathematical model was verified through experiments using a Nikon D750 and Nikkor 50 mm lens mounted on a car with varying speeds, object distances, and camera parameters. The results show that the mathematical model provides an accurate distance estimation of an object. The distance estimation error using the RSE due to the change in speed remained stable at approximately 10 cm. However, when the distance between the object and camera was more than 10 m, the estimated distance was sensitive to the RSE and the error increased dramatically.

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A two-step approach for the correction of rolling shutter distortion in UAV photogrammetry

Cited by 32 publications

References 18 publications

Determining optimal photogrammetric adjustment of images obtained from a fixed‐wing UAV

Determining optimal photogrammetric adjustment of images obtained from a fixed‐wing UAV

Automated 3D Reconstruction Using Optimized View-Planning Algorithms for Iterative Development of Structure-from-Motion Models

Object Distance Estimation Using a Single Image Taken from a Moving Rolling Shutter Camera

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