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

Pargieła, Karolina; Rzonca, A.

doi:10.1111/phor.12377

Cited by 9 publications

(10 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the application of such a solution requires time-consuming field measurements with care for the highest possible accuracy of determining the position of the points. Investment in time and human resources is associated with generating additional costs [27].…”

Section: Limitations Of Uav Systemsmentioning

confidence: 99%

“…Literature studies show that both multi-rotor [33,42,43] and fixed-wing [44][45][46] drones are used for measurement purposes, and the achieved accuracies can reach centimetre levels. For example, in the publication [27], multiple alignment variants of images acquired with a fixedwing FENIX UAV were analysed. The results obtained in the accuracy analysis are about 5 cm RMSE 3D in the best variant.…”

Section: Type Of Uav Usedmentioning

confidence: 99%

“…The use of cameras equipped with RS (Sony a6000) and GS (Sony RX1R II) was also analysed [27]. It showed that the use of distortion modelling for the RS allows accuracies to be obtained that are similar to those from a global shutter camera.…”

Section: Types Of Shutter Usedmentioning

confidence: 99%

See 2 more Smart Citations

Optimising UAV Data Acquisition and Processing for Photogrammetry: A Review

Pargieła

2023

GaEE

View full text Add to dashboard Cite

Unmanned aerial vehicles (UAVs) are used to acquire measurement data for an increasing number of applications. Photogrammetric studies based on UAV data, thanks to the significant development of computer vision techniques, photogrammetry, and equipment miniaturization, allow sufficient accuracy for many engineering and non-engineering applications to be achieved. In addition to accuracy, development time and cost of data acquisition and processing are also important issues. The aim of this paper is to present potential limitations in the use of UAVs to acquire measurement data and to present measurement and processing techniques affecting the optimisation of work both in terms of accuracy and economy. Issues related to the type of drones used (multi-rotor, fixed-wing), type of shutter in the camera (rolling shutter, global shutter ), camera calibration method (pre-calibration, self-calibration), georeferencing method (direct, indirect), technique of measuring the external images orientation parameters (RTK, PPK, PPP), flight design methods and the type of software used were analysed.

show abstract

Section: Limitations Of Uav Systemsmentioning

confidence: 99%

Section: Type Of Uav Usedmentioning

confidence: 99%

See 1 more Smart Citation

Optimising UAV Data Acquisition and Processing for Photogrammetry: A Review

Pargieła

2023

GaEE

View full text Add to dashboard Cite

show abstract

“…Three‐dimensional (3D) scene reconstruction plays an important role in generating geographic information data at different scales, such as city‐level, terrain‐level and component‐level scenes. It has emerged as a mainstream research area of computer vision (CV) and photogrammetry (Pargiela & Rzonca, 2021). In the context of urban scene reconstruction, the unmanned aerial vehicle (UAV) oblique photogrammetry method can generate fine 3D models with centimetre‐level resolutions.…”

Section: Introductionmentioning

confidence: 99%

A 3D urban scene reconstruction enhancement approach based on adaptive viewpoint selection of panoramic videos

Zhang,

Hu,

et al. 2024

The Photogrammetric Record

View full text Add to dashboard Cite

The widely used unmanned aerial vehicle oblique photogrammetry often suffers from information loss in complex urban environments, leading to geometric and textural defects in the resulting models. In this study, a close‐range panoramic optimal viewpoint selection assisted 3D urban scene reconstruction enhancement method is proposed for areas prone to defects. We first introduce the ground panoramic data acquisition equipment and strategy, which are different from those of the single‐lens supplementary photography method. Data acquisition is accomplished through a single and continuous surround‐style collection approach. The full coverage of the panoramic video in the space–time dimension enables the acquisition of texture details without considering camera station planning. Then, a panoramic multiview image generation approach is proposed. Adaptive viewpoint selection is achieved using unbiased sampling points from the rough scene model, and viewpoint optimisation is adopted to ensure sufficient image overlap and intersection effects, thus improving the scene reconstructability. Finally, the 3D model is generated by photogrammetric processing of the panoramic multiview images, resulting in an enhanced modelling effect. To validate the proposed method, we conducted experiments using real data from Qingdao, China. Both the qualitative and quantitative results demonstrate a significant improvement in the quality of geometric and textural reconstruction. The tie‐point reprojection errors are less than 1 pixel, and the registration accuracy with the model from oblique photogrammetry is comparable to that of optimised‐view photography. By eliminating the need for on‐site camera station planning or manual flight operations and effectively minimising the redundancy of panoramic videos, our approach significantly reduces the photography and computation costs associated with reconstruction enhancement. Thus, it presents a feasible technical solution for the generation of urban 3D fine models.

show abstract

“…However, these methods are constrained by the sensor capabilities and distances reflected on temporal and spatial resolution of the images, which results in its hard‐to‐reach fine‐grained and millimetre‐level accuracy in the detection of specific urban targets (Li et al., 2020). In contrast, contemporary UAV platforms in the mapping industry—such as DJI P4 RTK, Mavic 3E and M300RTK—incorporate advanced Global Navigation Satellite System and real‐time kinematic (RTK) technologies to ensure centimetre‐level position accuracy of the geolocation (Pargieła & Rzonca, 2021). Meanwhile, the three‐axis gimbal stabilization ensures image clarity during the flight.…”

Section: Introductionmentioning

confidence: 99%

Linear target change detection from a single image based on three‐dimensional real scene

Liu,

Ji,

Chen

et al. 2023

The Photogrammetric Record

View full text Add to dashboard Cite

Change detection is a critical component in the field of remote sensing, with significant implications for resource management and land monitoring. Currently, most conventional methods for remote sensing change detection often rely on qualitative monitoring, which usually requires data collection from the entire scene over multiple time periods. In this paper, we propose a method that can be computationally intensive and lacks reusability, especially when dealing with large datasets. We use a novel methodology that leverages the texture features and geometric structure information derived from three‐dimensional (3D) real scenes. By establishing a two‐dimensional (2D)–3D geometric relationship between a single observational image and the corresponding 3D scene, we can obtain more accurate positional information for the image. This relationship allows us to transfer the depth information from the 3D model to the observational image, thereby facilitating precise geometric change measurements for specific planar targets. Experimental results indicate that our approach enables millimetre‐level change detection of minuscule targets based on a single image. Compared with conventional methods, our technique offers enhanced efficiency and reusability, making it a valuable tool for the fine‐grained change detection of small targets based on 3D real scene.

show abstract

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

Cited by 9 publications

References 59 publications

Optimising UAV Data Acquisition and Processing for Photogrammetry: A Review

Optimising UAV Data Acquisition and Processing for Photogrammetry: A Review

A 3D urban scene reconstruction enhancement approach based on adaptive viewpoint selection of panoramic videos

Linear target change detection from a single image based on three‐dimensional real scene

Contact Info

Product

Resources

About