Using Information Content to Select Keypoints for UAV Image Matching

Mousavi, Vahid; Varshosaz, Masood; Remondino, Fabio

doi:10.3390/rs13071302

Cited by 19 publications

(13 citation statements)

References 43 publications

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“…Tie points are extracted from the image sets and then the influence of tie point distribution and numbers are analysed considering the outcomes of the bundle adjustment. As no ground control / truth is available, following Remondino et al, 2017 andMousavi et al (2021), three criteria at the end of the bundle adjustment are considered:…”

Section: Evaluation Methodologymentioning

confidence: 99%

Evaluating Tie Points Distribution, Multiplicity and Number on the Accuracy of Uav Photogrammetry Blocks

Mousavi

Varshosaz

Remondino

2021

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

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Abstract. Image orientation is a fundamental task in photogrammetric applications and it is performed by extracting keypoints with hand-crafted or learning-based methods, generating tie points among the images and running a bundle adjustment procedure. Nowadays, due to large number of extracted keypoints, tie point filtering approaches attempt to eliminate redundant tie points in order to increase accuracy and reduce processing time. This paper presents the results of an investigation concerning tie points impact on bundle adjustment results. Simulations and real data are processed in Australis and DBAT to evaluate different affecting factors, including tie point numbers, location accuracy, distribution and multiplicity. Achieved results show that increasing the amount of tie points improve the quality of bundle adjustment results, provided that the tie points are well-distributed on the image. Furthermore, bundle adjustment quality is improved as the multiplicity of tie points increases and their location uncertainty decrease. Based on simulation results, some suggestions for accurate tie points filtering in typical UAV photogrammetry blocks cases are derived.

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Section: Evaluation Methodologymentioning

confidence: 99%

Evaluating Tie Points Distribution, Multiplicity and Number on the Accuracy of Uav Photogrammetry Blocks

Mousavi

Varshosaz

Remondino

2021

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

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“…Although UAV photogrammetry has been considered as a popular option for the digital modeling of bridges, several concerns in the UAV photogrammetry pipeline, including the path planning to cover blind spots [60], the quality of image matching process [61], the accuracy of image orientation [62], and the geometric accuracy of reconstructed models [54], require to be effectively addressed. In addition, as the two techniques of TLS and UAV photogrammetry have been widely used for DT generation, several studies compared the accuracy of these two methods [63,64].…”

Section: • Uav Photogrammetrymentioning

confidence: 99%

Evolution of Digital Twin Frameworks in Bridge Management: Review and Future Directions

Mousavi,

Rashidi,

Mohammadi

et al. 2024

Remote Sensing

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Over the last decade, the digital twin (DT) concept has effectively revolutionized conventional bridge monitoring and management. Despite their overall success, current bridge DTs encounter conceptual ambiguities, hindering their inherent potential for practical implementation. Moreover, intelligent decision support models have not been properly considered as a component of the bridge DTs framework to enhance the reliability of decisions for asset maintenance. Therefore, this paper conducts a scientometric analysis and a comprehensive state-of-the-art review, exploring current bridge DT research trends and architectures and introducing an enhanced conceptual framework for bridge DTs. To this end, more than 480 research publications have been reviewed, compared, and analyzed. The research result encompasses the redevelopment of a multilayer DT framework, fostering its implementation in the full lifecycle of bridge infrastructure while exploring the potential integration of decision support systems and data fusion from advanced technologies to improve the overall efficiency of implementing DT technology in bridges.

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“…Automatic Arial Triangulation (AAT) is conducted as a standard technique in UAV photogrammetry which is performed through tie points extraction (Mousavi, 2021a). The quality of selected tie points is an important and influential factor in the accuracy and quality of products generated using UAV photogrammetry (Mousavi, 2021b). To accurately extract an adequate number of tie points, it is necessary to design an imaging network before concluding photogrammetry operations with UAVs (Saadatseresht, 2015).…”

Section: Introductionmentioning

confidence: 99%

Comparison of Uav Image Spatial Resolution Based on the Siemens Star Target

Fakhri

Motayyeb²,

Saadatseresht³

et al. 2023

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. In recent years, as the use of Unmanned Aerial Vehicle (UAV) imaging systems has increased, the photogrammetry community has conducted extensive research on the unique advantages of these systems. The UAVs are considered as one of the most important platforms for photogrammetry applications from various urban and non-urban areas at different scales. In UAV photogrammetry projects the spatial resolution of the images must be determined prior to the imaging stage. The spatial resolution of the images is a commonly-used criterion for detecting the smallest distance between two adjacent separable objects in the images. Numerous methods have been developed to precisely evaluate the spatial resolution of images. In this study, the Siemens star target, which is one of the most commonly used artificial targets for analysing spatial resolution was studied. The objective of this paper is to evaluate and compare the reduction of spatial resolution coefficient using the Siemens star target in images captured by UAVs. To this end, a method for automatically detecting the radius of the circle of ambiguity and calculating spatial resolution in UAV images has been developed. According to the findings of this study, the initial step in creating the Siemens star target, in terms of size and the number of acceptable arms, is dependent on the flying altitude of the UAV and the level of image blur. In addition, the reduction in spatial resolution of images captured by various UAVs varies, and its coefficient must be calculated for each project.

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Using Information Content to Select Keypoints for UAV Image Matching

Cited by 19 publications

References 43 publications

Evaluating Tie Points Distribution, Multiplicity and Number on the Accuracy of Uav Photogrammetry Blocks

Evaluating Tie Points Distribution, Multiplicity and Number on the Accuracy of Uav Photogrammetry Blocks

Evolution of Digital Twin Frameworks in Bridge Management: Review and Future Directions

Comparison of Uav Image Spatial Resolution Based on the Siemens Star Target

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