Comparative Analysis of Different UAV-Based Photogrammetric Processes to Improve Product Accuracies

Saponaro, Mirko; Capolupo, Alessandra; Tarantino, Eufemia; Fratino, Umberto

doi:10.1007/978-3-030-24305-0_18

Cited by 13 publications

(13 citation statements)

References 14 publications

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“…The results obtained can be considered as in line with those already discussed in previous works [ 11 , 18 ], in which it was possible to see a coherent trend of RMSE values for DG and complete IG cases, especially about the elbow point of the statistic curve in a range of GCPs implemented equal to 5–7. Considering a different application scenario and a flight altitude of 120 m, in Agüera-Vega et al [ 17 ] the trends obtained in this work were confirmed by recording a reduction of both planar and vertical RMSE values around the seventh GCP implemented, while the lowest values were recorded in the configuration with 15 GCPs.…”

Section: Resultssupporting

confidence: 91%

“…After structuring the overall processing workflow, the processing pipelines were carefully parameterized to make them comparable in both licensed and open source softwares. For the best interpretation of the results derived from the generation of point clouds processed from the same set of image data, through statistical inference, the influence on the final product accuracy of the number of Ground Control Points (GCP) implemented in the georeferencing was then analyzed [ 11 ]. The tests carried out were aimed at investigating the elements shared by the platforms tested, with the purpose of supporting future studies to define a single index for the accuracy of final products.…”

Section: Introductionmentioning

confidence: 99%

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Parallel Development of Comparable Photogrammetric Workflows Based on UAV Data Inside SW Platforms

Saponaro

Turso²,

Tarantino

2020

Computational Science and Its Applications – ICCSA 2020

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A wide range of industrial applications benefits from the accessibility of image-based techniques for three-dimensional modelling of different multi-scale objects. In the last decade, along with the technological progress mainly achieved with the use of Unmanned Aerial Vehicles (UAVs), there has been an exponential growth of software platforms enabled to return photogrammetric products. On the other hand, the different levels of final product accuracy resulting from the adoption of different processing approaches in various softwares have not yet been fully understood. To date, there is no validation analysis in literature focusing on the comparability of such products, not even in relation to the use of workflows commonly allowed inside various software platforms. The lack of detailed information about the algorithms implemented in the licensed platforms makes the whole interpretation even more complex. This work therefore aims to provide a comparative evaluation of three photogrammetric softwares commonly used in the industrial field, in order to obtain coherent, if not exactly congruent results. After structuring the overall processing workflow, the processing pipelines were accurately parameterized to make them comparable in both licensed and open-source softwares. For the best interpretation of the results derived from the generation of point clouds processed by the same image dataset, the obtainable values of root-mean-square error (RMSE) were analyzed, georeferencing models as the number of GCPs varied. The tests carried out aimed at investigating the elements shared by the platforms tested, with the purpose of supporting future studies to define a unique index for the accuracy of final products.

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Section: Resultssupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Parallel Development of Comparable Photogrammetric Workflows Based on UAV Data Inside SW Platforms

Saponaro

Turso²,

Tarantino

2020

Computational Science and Its Applications – ICCSA 2020

Self Cite

View full text Add to dashboard Cite

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“…These findings are also supported by the statistics (ME and RMSE) reported in Table 3. In all examined setups, ME and RMSE are in line with the standards defined by ASPRS for the digital production of cartographic data (American Society for Photogrammetry and Remote Sensing (ASPRS), 2015; Saponaro et al, 2019b) concerning the different georeferencing strategies. Although affected by a greater computational effort with a reduction of manual operations, the co-alignment procedure returns geometrically robust products (Table 3).…”

Section: Photogrammetric Outcomessupporting

confidence: 71%

Influence of Co-Alignment Procedures on the Co-Registration Accuracy of Multi-Epoch SFM Points Clouds

Saponaro

Capolupo

Caporusso

et al. 2021

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The well-established spread of Remotely Piloted Aircraft Systems (RPAS) as high-performance devices in the acquisition of huge datasets has found a fertile field in the geomorphological change detection in coastal areas. The ability to retrieve image datasets with multi-epoch frequency makes them effectively incisive for planning ongoing monitoring. Considering the wide accessibility to multiple Structure-from-Motion (SfM)-3D point clouds, it follows the need for their proper management to identify a profitable co-registration approach valid for a proper comparison among them. In most cases the co-registration is inherited from the same georeferencing; in other cases, it can be done manually. Unfortunately, these methodologies are time consuming and often do not properly consider geometric errors on the models. The purpose of this research work was therefore to analyse an alternative method such as the co-alignment of sparse point clouds. Given the independently or co-aligned processed multi-epoch datasets, mean errors (ME) and root-mean-square error (RMSE) on Check Points (CPs) were evaluated by adopting different georeferencing strategies. Lastly, by first generating dense point clouds and from these the Digital Elevation Models (DEMs), scalar fields regarding DEM of Differences (DoD) were computed and allowed to localize any uncertainties δz among the estimated elevations. A cloud-to-cloud comparison was obtained using the M3C2 algorithm to extrapolate systematic georeferencing errors and the local deviation between models, an evidence of how the method can affect the detectable changes. The co-alignment methodology showed encouraging results proving to be a valid alternative to more traditional approaches.

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“…Generally, these analyses are based on performing the full analysis pipeline and comparing the results to a known ground truth. In (Saponaro et al, 2019), (Roberts et al, 2017) and (Cwiakala, 2019) the authors test reconstruction performance on real images from UAS missions, while in (Hoppe et al, 2012), (Peng and Isler, 2019) and (Koch et al, 2019) simulated images are used. In all these cases, a 3D reconstruction with SfM is computed and certain points are compared to their kown true position.…”

Section: Existing Approachesmentioning

confidence: 99%

Evaluation of 3d Uas Flight Path Planning Algorithms

Debus

Rodehorst

2021

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The application of image-based methods in inspections and monitoring has increased significantly over recent years. This is especially the case for the inspection of large structures that are not easily accessible for human inspectors. Here, unmanned aircraft systems (UAS) can support by generating high-quality images, that contain valuable information about the structure’s condition. To guarantee high quality and completeness for the acquired data, inspection missions are planned in advance by computing a flight path for the UAS, that covers the entire structure with the required quality. Many approaches on this topic exist that aim to solve this planning task. Nevertheless, each publication on this matter mostly stands on its own, working with its own criteria and no comparison to other approaches. Therefore, it is currently not possible to compare different approaches and select the most suitable for a specific scenario. To solve this problem, this work proposes an evaluation pipeline that applies well defined quality criteria on flight paths for close-range image-based inspections. These criteria are limited to fundamental aspects for the evaluation of paths that were created for diverse scenarios with diverse criteria and still find common ground for comparison. As experiments show, this pipeline allows the comparison of different approaches, objectifying the performance and working towards a common understanding of the current state of the art. Finally, the Bauhaus Path Planning Challenge is presented, inviting submissions to a comparison based on this pipeline to collaborate on an objective ranking, available under https://uni-weimar.de/pathplanning.

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Comparative Analysis of Different UAV-Based Photogrammetric Processes to Improve Product Accuracies

Cited by 13 publications

References 14 publications

Parallel Development of Comparable Photogrammetric Workflows Based on UAV Data Inside SW Platforms

Parallel Development of Comparable Photogrammetric Workflows Based on UAV Data Inside SW Platforms

Influence of Co-Alignment Procedures on the Co-Registration Accuracy of Multi-Epoch SFM Points Clouds

Evaluation of 3d Uas Flight Path Planning Algorithms

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