Uav Linear Photogrammetry

Tournadre, Vincent; Pierrot-Deseilligny, Marc; Faure, Paul-Henri

doi:10.5194/isprsarchives-xl-3-w3-327-2015

Cited by 32 publications

(35 citation statements)

References 13 publications

(8 reference statements)

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“…Linear sequences of images have been shown to yield warped 3D models due to a drift in bundle adjustment [25,26].…”

Section: Effects Of the Refined Distortion Model On Micmac Processingmentioning

confidence: 99%

“…Before processing data with MicMac based on the different scenarios, the MicMac module for UAV linear photogrammetry [25] has been put to the test. These additional distortion models integrated into MicMac have been developed for long linear surveys, especially for riverbed monitoring over several kilometers.…”

Section: Effects Of the Refined Distortion Model On Micmac Processingmentioning

confidence: 99%

“…The distortion model used in this module is a Fraser's radial model with decentric and affine parameters and 12 degrees of freedom. Recently, Tournadre et al (2015) published a study [25] presenting the last evolutions of MicMac's bundle adjustment and some additional camera distortion models specifically designed to address issues arising with UAV linear photogrammetry. Indeed, UAV surveys along a linear trajectory may be problematic for 3D reconstruction, as they tend to induce "bowl effects" [25,26] due to a poor estimation of the camera's internal parameters.…”

mentioning

confidence: 99%

“…Recently, Tournadre et al (2015) published a study [25] presenting the last evolutions of MicMac's bundle adjustment and some additional camera distortion models specifically designed to address issues arising with UAV linear photogrammetry. Indeed, UAV surveys along a linear trajectory may be problematic for 3D reconstruction, as they tend to induce "bowl effects" [25,26] due to a poor estimation of the camera's internal parameters. This study therefore puts to the test the refined radial distortion model "Four 15ˆ2" [23,25] for camera distortion.…”

mentioning

confidence: 99%

“…Indeed, UAV surveys along a linear trajectory may be problematic for 3D reconstruction, as they tend to induce "bowl effects" [25,26] due to a poor estimation of the camera's internal parameters. This study therefore puts to the test the refined radial distortion model "Four 15ˆ2" [23,25] for camera distortion. Using GCPs, the image relative orientations are transformed with "GCP Bascule" into an absolute orientation within the local coordinate system.…”

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confidence: 99%

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Assessing the Accuracy of High Resolution Digital Surface Models Computed by PhotoScan® and MicMac® in Sub-Optimal Survey Conditions

et al. 2016

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Abstract:For monitoring purposes and in the context of geomorphological research, Unmanned Aerial Vehicles (UAV) appear to be a promising solution to provide multi-temporal Digital Surface Models (DSMs) and orthophotographs. There are a variety of photogrammetric software tools available for UAV-based data. The objective of this study is to investigate the level of accuracy that can be achieved using two of these software tools: Agisoft PhotoScan ® Pro and an open-source alternative, IGN © MicMac ® , in sub-optimal survey conditions (rugged terrain, with a large variety of morphological features covering a range of roughness sizes, poor GPS reception). A set of UAV images has been taken by a hexacopter drone above the Rivière des Remparts, a river on Reunion Island. This site was chosen for its challenging survey conditions: the topography of the study area (i) involved constraints on the flight plan; (ii) implied errors on some GPS measurements; (iii) prevented an optimal distribution of the Ground Control Points (GCPs) and; (iv) was very complex to reconstruct. Several image processing tests are performed with different scenarios in order to analyze the sensitivity of each software package to different parameters (image quality, numbers of GCPs, etc.). When computing the horizontal and vertical errors within a control region on a set of ground reference targets, both methods provide rather similar results. A precision up to 3-4 cm is achievable with these software packages. The DSM quality is also assessed over the entire study area comparing PhotoScan DSM and MicMac DSM with a Terrestrial Laser Scanner (TLS) point cloud. PhotoScan and MicMac DSM are also compared at the scale of particular features. Both software packages provide satisfying results: PhotoScan is more straightforward to use but its source code is not open; MicMac is recommended for experimented users as it is more flexible.

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“…Linear sequences of images have been shown to yield warped 3D models due to a drift in bundle adjustment [25,26].…”

Section: Effects Of the Refined Distortion Model On Micmac Processingmentioning

confidence: 99%

Section: Effects Of the Refined Distortion Model On Micmac Processingmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Assessing the Accuracy of High Resolution Digital Surface Models Computed by PhotoScan® and MicMac® in Sub-Optimal Survey Conditions

et al. 2016

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Structure from motion photogrammetry in ecology: Does the choice of software matter?

Forsmoo

Anderson

Macleod

et al. 2019

Ecology and Evolution

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Image‐based modeling, and more precisely, Structure from Motion (SfM) and Multi‐View Stereo (MVS), is emerging as a flexible, self‐service, remote sensing tool for generating fine‐grained digital surface models (DSMs) in the Earth sciences and ecology. However, drone‐based SfM + MVS applications have developed at a rapid pace over the past decade and there are now many software options available for data processing. Consequently, understanding of reproducibility issues caused by variations in software choice and their influence on data quality is relatively poorly understood. This understanding is crucial for the development of SfM + MVS if it is to fulfill a role as a new quantitative remote sensing tool to inform management frameworks and species conservation schemes. To address this knowledge gap, a lightweight multirotor drone carrying a Ricoh GR II consumer‐grade camera was used to capture replicate, centimeter‐resolution image datasets of a temperate, intensively managed grassland ecosystem. These data allowed the exploration of method reproducibility and the impact of SfM + MVS software choice on derived vegetation canopy height measurement accuracy. The quality of DSM height measurements derived from four different, yet widely used SfM‐MVS software—Photoscan, Pix4D, 3DFlow Zephyr, and MICMAC, was compared with in situ data captured on the same day as image capture. We used both traditional agronomic techniques for measuring sward height, and a high accuracy and precision differential GPS survey to generate independent measurements of the underlying ground surface elevation. Using the same replicate image dataset (n = 3) as input, we demonstrate that there are 1.7, 2.0, and 2.5 cm differences in RMSE (excluding one outlier) between the outputs from different SfM + MVS software using High, Medium, and Low quality settings, respectively. Furthermore, we show that there can be a significant difference, although of small overall magnitude between replicate image datasets (n = 3) processed using the same SfM + MVS software, following the same workflow, with a variance in RMSE of up to 1.3, 1.5, and 2.7 cm (excluding one outlier) for “High,” “Medium,” and “Low” quality settings, respectively. We conclude that SfM + MVS software choice does matter, although the differences between products processed using “High” and “Medium” quality settings are of small overall magnitude.

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Mitigating systematic error in topographic models for geomorphic change detection: accuracy, precision and considerations beyond off‐nadir imagery

James

Antoniazza

Robson

et al. 2020

Earth Surf Processes Landf

111

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Unmanned aerial vehicles (UAVs) and structure-from-motion photogrammetry enable detailed quantification of geomorphic change. However, rigorous precision-based change detection can be compromised by survey accuracy problems producing systematic topographic error (e.g. 'doming'), with error magnitudes greatly exceeding precision estimates. Here, we assess survey sensitivity to systematic error, directly correcting topographic data so that error magnitudes align more closely with precision estimates. By simulating conventional grid-style photogrammetric aerial surveys, we quantify the underlying relationships between survey accuracy, camera model parameters, camera inclination, tie point matching precision and topographic relief, and demonstrate a relative insensitivity to image overlap. We show that a current doming-mitigation strategy of using a gently inclined (<15°) camera can reduce accuracy by promoting a previously unconsidered correlation between decentring camera lens distortion parameters and the radial terms known to be responsible for systematic topographic error. This issue is particularly relevant for the wide-angle cameras often integrated into current-generation, accessible UAV systems, frequently used in geomorphic research. Such systems usually perform on-board image pre-processing, including applying generic lens distortion corrections, that subsequently alter parameter interrelationships in photogrammetric processing (e.g. partially correcting radial distortion, which increases the relative importance of decentring distortion in output images). Surveys from two proglacial forefields (Arolla region, Switzerland) showed that results from lower-relief topography with a 10°-inclined camera developed vertical systematic doming errors > 0•3 m, representing accuracy issues an order of magnitude greater than precision-based error estimates. For higher-relief topography, and for nadir-imaging surveys of the lower-relief topography, systematic error was < 0•09 m. Modelling and subtracting the systematic error directly from the topographic data successfully reduced error magnitudes to values consistent with twice the estimated precision. Thus, topographic correction can provide a more robust approach to uncertainty-based detection of event-scale geomorphic change than designing surveys with small off-nadir camera inclinations and, furthermore, can substantially reduce ground control requirements.

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Uav Linear Photogrammetry

Cited by 32 publications

References 13 publications

Assessing the Accuracy of High Resolution Digital Surface Models Computed by PhotoScan® and MicMac® in Sub-Optimal Survey Conditions

Assessing the Accuracy of High Resolution Digital Surface Models Computed by PhotoScan® and MicMac® in Sub-Optimal Survey Conditions

Structure from motion photogrammetry in ecology: Does the choice of software matter?

Mitigating systematic error in topographic models for geomorphic change detection: accuracy, precision and considerations beyond off‐nadir imagery

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