Analysis of 3D Accuracy According to Determination of Calibration Initial Value in Close-Range Digital Photogrammetry Using VLBI Antenna and Mobile Phone Camera

김혁길,; 윤홍식,; 조재명,

doi:10.7848/ksgpc.2015.33.1.31

Cited by 4 publications

(4 citation statements)

References 2 publications

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“…depth cameras) can automatically produce 3D point cloud data, a precise pre-calibration procedure is required to determine their interior orientation parameters and the relative ones between them. Besides, these parameters may change because of internal instability or external factors (Kim and Choi, 2021). Even when a simple compact camera is used for CRP, they tend to be pre-calibrated using a calibration grid (e.g.…”

Section: 1mentioning

confidence: 99%

A close-range photogrammetric model for tracking and performance-based forecasting earthmoving operations

Saif

Alshibani

2023

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Purpose This paper aims to present a highly accessible and affordable tracking model for earthmoving operations in an attempt to overcome some of the limitations of current tracking models. Design/methodology/approach The proposed methodology involves four main processes: acquiring onsite terrestrial images, processing the images into 3D scaled cloud data, extracting volumetric measurements and crew productivity estimations from multiple point clouds using Delaunay triangulation and conducting earned value/schedule analysis and forecasting the remaining scope of work based on the estimated performance. For validation, the tracking model was compared with an observation-based tracking approach for a backfilling site. It was also used for tracking a coarse base aggregate inventory for a road construction project. Findings The presented model has proved to be a practical and accurate tracking approach that algorithmically estimates and forecasts all performance parameters from the captured data. Originality/value The proposed model is unique in extracting accurate volumetric measurements directly from multiple point clouds in a developed code using Delaunay triangulation instead of extracting them from textured models in modelling software which is neither automated nor time-effective. Furthermore, the presented model uses a self-calibration approach aiming to eliminate the pre-calibration procedure required before image capturing for each camera intended to be used. Thus, any worker onsite can directly capture the required images with an easily accessible camera (e.g. handheld camera or a smartphone) and can be sent to any processing device via e-mail, cloud-based storage or any communication application (e.g. WhatsApp).

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Section: 1mentioning

confidence: 99%

A close-range photogrammetric model for tracking and performance-based forecasting earthmoving operations

Saif

Alshibani

2023

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“…To acquire extensive 3D spatial data, aerial laser scanning (ALS) or terrestrial laser scanning (TLS) methodologies utilizing light detection and ranging (LiDAR) instruments are deployed across multiple stations, necessitating the registration of survey outcomes from each station. This process is particularly crucial in indoor environments with many occluded areas, thus necessitating the use of multiple stations [1][2][3]. Point cloud registration is also necessary when using LiDAR surveying to collect data in a vast outdoor area [4].…”

Section: Introduction 1backgroundmentioning

confidence: 99%

Coarse Alignment Methodology of Point Cloud Based on Camera Position/Orientation Estimation Model

Yoo,

Kim

2023

J. Imaging

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This study presents a methodology for the coarse alignment of light detection and ranging (LiDAR) point clouds, which involves estimating the position and orientation of each station using the pinhole camera model and a position/orientation estimation algorithm. Ground control points are obtained using LiDAR camera images and the point clouds are obtained from the reference station. The estimated position and orientation vectors are used for point cloud registration. To evaluate the accuracy of the results, the positions of the LiDAR and the target were measured using a total station, and a comparison was carried out with the results of semi-automatic registration. The proposed methodology yielded an estimated mean LiDAR position error of 0.072 m, which was similar to the semi-automatic registration value of 0.070 m. When the point clouds of each station were registered using the estimated values, the mean registration accuracy was 0.124 m, while the semi-automatic registration accuracy was 0.072 m. The high accuracy of semi-automatic registration is due to its capability for performing both coarse alignment and refined registration. The comparison between the point cloud with refined alignment using the proposed methodology and the point-to-point distance analysis revealed that the average distance was measured at 0.0117 m. Moreover, 99% of the points exhibited distances within the range of 0.0696 m.

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“…(9) and (10)의 분자와 분모에 각각 나누어 Eqs. (11) and 12의 형태로 변환 시킨다. 여기서, 사진좌표계에서의 축에 대한 초점거 리는   이고, 축에 대한 초점거리가   가 된다.…”

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“…Eqs. (11) and 12 Figure 8. Convergence tendencies of (XL, YL, ZL) by bundle adjustment in the first image Figure 9.…”

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confidence: 99%

Accuracy Analysis of 3D Position of Close-range Photogrammetry Using Direct Linear Transformation and Self-calibration Bundle Adjustment with Additional Parameters

Kim¹,

Hwang²,

Yun³

2015

Journal of Korean Society for Geospatial Information System

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In this study, the 3D position coordinates were calculated for the targets using DLT and self-calibration bundle adjustment with additional parameters in close-range photogrammetry. And then, the accuracy of the results were analysed. For this purpose, the results of camera calibration and orientation parameters were calculated for each images by performing reference surveying using total station though the composition of experimental conditions attached numerous targets. To analyze the accuracy, 3D position coordinates were calculated for targets that has been identically selected and compared with the reference coordinates obtained from a total station. For the image coordinate measurement of the stereo images, we performed the ellipse fitting procedure for measuring the center point of the circular target. And then, the results were utilized for the image coordinate for targets. As a results from experiments, position coordinates calculated by the stereo images-based photogrammetry have resulted out the deviation of less than an average 4mm within the maximum error range of less than about 1cm. From this result, it is expected that the stereo images-based photogrammetry would be used to field of various close-range photogrammetry required for precise accuracy.

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Analysis of 3D Accuracy According to Determination of Calibration Initial Value in Close-Range Digital Photogrammetry Using VLBI Antenna and Mobile Phone Camera

Cited by 4 publications

References 2 publications

A close-range photogrammetric model for tracking and performance-based forecasting earthmoving operations

A close-range photogrammetric model for tracking and performance-based forecasting earthmoving operations

Coarse Alignment Methodology of Point Cloud Based on Camera Position/Orientation Estimation Model

Accuracy Analysis of 3D Position of Close-range Photogrammetry Using Direct Linear Transformation and Self-calibration Bundle Adjustment with Additional Parameters

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