• Title/Summary/Keyword: digital close-range photogrammetry

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Assessment of a smartphone-based monitoring system and its application

  • Ahn, Hoyong;Choi, Chuluong;Yu, Yeon
    • Korean Journal of Remote Sensing
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    • v.30 no.3
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    • pp.383-397
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    • 2014
  • Information technology advances are allowing conventional surveillance systems to be combined with mobile communication technologies, creating ubiquitous monitoring systems. This paper proposes monitoring system that uses smart camera technology. We discuss the dependence of interior orientation parameters on calibration target sheets and compare the accuracy of a three-dimensional monitoring system with camera location calculated by space resectioning using a Digital Surface Model (DSM) generated from stereo images. A monitoring housing is designed to protect a camera from various weather conditions and to provide the camera for power generated from solar panel. A smart camera is installed in the monitoring housing. The smart camera is operated and controlled through an Android application. At last the accuracy of a three-dimensional monitoring system is evaluated using a DSM. The proposed system was then tested against a DSM created from ground control points determined by Global Positioning Systems (GPSs) and light detection and ranging data. The standard deviation of the differences between DSMs are less than 0.12 m. Therefore the monitoring system is appropriate for extracting the information of objects' position and deformation as well as monitoring them. Through incorporation of components, such as camera housing, a solar power supply, the smart camera the system can be used as a ubiquitous monitoring system.

Fundamental behavior of CFT beam-columns under fire loading

  • Varma, Amit H.;Hong, Sangdo;Choe, Lisa
    • Steel and Composite Structures
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    • v.15 no.6
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    • pp.679-703
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    • 2013
  • This paper presents experimental investigations of the fundamental behavior of concrete filled steel tube (CFT) beam-columns under fire loading. A total of thirteen specimens were tested to determine the axial force-moment-curvature-temperature behavior of CFT beam-columns. The experimental approach involved the use of: (a) innovative heating and control equipment to apply thermal loading and (b) digital image correlation with close-range photogrammetry to measure the deformations (e.g., curvature) of the heated region. Each specimen was sequentially subjected to: (i) constant axial loading; (ii) thermal loading in the expected plastic hinge region following the ASTM E119 temperature-time T-t curve; and (iii) monotonically increasing flexural loading. The effects of various parameters on the strength and stiffness of CFT beam-columns were evaluated. The parameters considered were the steel tube width, width-tothickness ratio, concrete strength, maximum surface temperature of the steel tube, and the axial load level on the composite CFT section. The experimental results provide knowledge of the fundamental behavior of composite CFT beam-columns, and can be used to calibrate analytical models or macro finite element models developed for predicting behavior of CFT members and frames under fire loading.

Application of Smartphone Camera Calibration for Close-Range Digital Photogrammetry (근접수치사진측량을 위한 스마트폰 카메라 검보정)

  • Yun, MyungHyun;Yu, Yeon;Choi, Chuluong;Park, Jinwoo
    • Korean Journal of Remote Sensing
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    • v.30 no.1
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    • pp.149-160
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    • 2014
  • Recently studies on application development and utilization using sensors and devices embedded in smartphones have flourished at home and abroad. This study aimed to analyze the accuracy of the images of smartphone to determine three-dimension position of close objects prior to the development of photogrammetric system applying smartphone and evaluate the feasibility to use. First of all, camera calibration was conducted on autofocus and infinite focus. Regarding camera calibration distortion model with balance system and unbalance system was used for the decision of lens distortion coefficient, the results of calibration on 16 types of projects showed that all cases were in RMS error by less than 1 mm from bundle adjustment. Also in terms of autofocus and infinite focus on S and S2 model, the pattern of distorted curve was almost the same, so it could be judged that change in distortion pattern according to focus mode is very little. The result comparison according to autofocus and infinite focus and the result comparison according to a software used for multi-image processing showed that all cases were in standard deviation less than ${\pm}3$ mm. It is judged that there is little result difference between focus mode and determination of three-dimension position by distortion model. Lastly the checkpoint performance by total station was fixed as most probable value and the checkpoint performance determined by each project was fixed as observed value to calculate statistics on residual of individual methods. The result showed that all projects had relatively large errors in the direction of Y, the direction of object distance compared to the direction of X and Z. Like above, in terms of accuracy for determination of three-dimension position for a close object, the feasibility to use smartphone camera would be enough.

A Experimental Study on the 3-D Image Restoration Technique of Submerged Area by Chung-ju Dam (충주댐 수몰지구의 3차원 영상복원 기법에 관한 실험적 연구)

  • 연상호
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.22 no.1
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    • pp.21-27
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    • 2004
  • It will be a real good news fer the people who were lost their hometown by the construction of a large dam to be restored to the farmer state. Focused on Cheung-pyung around where most part were submerged by the Chungju large Dam founded in eurly 1980s, It used remote sensing image restoration Technique in this study in order to restore topographical features before the flood with stereo effects. We gathered comparatively good satellite photos and remotely sensed digital images, then its made a new fusion image from these various satellite images and the topographical map which had been made before the water filled by the DAM. This task was putting together two kinds of different timed images. And then, we generated DEM including the outskirts of that area as matching current contour lines with the map. That could be a perfect 3D image of test areas around before when it had been water filled by making perspective images from all directions included north, south, east and west, fer showing there in 3 dimensions. Also, for close range visiting made of flying simulation can bring to experience their real space at that time. As a result of this experimental task, it made of new fusion images and 3-D perspective images and simulation live images by remotely sensed photos and images, old paper maps about vanished submerged Dam areas and gained of possibility 3-D terrain image restoration about submerged area by large Dam construction.

True Orthoimage Generation from LiDAR Intensity Using Deep Learning (딥러닝에 의한 라이다 반사강도로부터 엄밀정사영상 생성)

  • Shin, Young Ha;Hyung, Sung Woong;Lee, Dong-Cheon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.4
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    • pp.363-373
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    • 2020
  • During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.