This study aimed to investigate the usability of smartphone camera images in 3D positioning applications with photogrammetric techniques. These investigations were performed in two stages. In the first stage, the cameras of five smartphones and a digital compact camera were calibrated using a calibration reference object, with signalized points having known three-dimensional (3D) coordinates. In the calibration process, the self-calibration bundle adjustment method was used. To evaluate the metric performances, the geometric accuracy tests in the image and object spaces were performed and the test results were compared. In the second stage, a 3D mesh model of a historical cylindrical structure (height = 8 m and diameter = 5 m) was generated using Structure-from-Motion and Multi-View-Stereo (SfM-MVS) approach. The images were captured using the Galaxy S4 smartphone camera, which produced the best result in the geometric accuracy tests for smartphone cameras. The accuracy tests on the generated 3D model were also applied in order to examine 3D object reconstruction capabilities of imaging with this device. The results demonstrated that smartphone cameras can be easily used as image acquisition tools for multiple photogrammetric applications.
In photogrammetric applications, camera calibration and orientation procedures are a prerequisite for the extraction of precise and reliable 3D metric information from images. This study presents a method for full automatic calibration of color digital cameras using color targets. Software developed using Borland C + + Builder programming language is used to apply the method. With this software, the calibration process is carried out in 3 stages: firstly, at least four of six color targets (whose 3D object coordinates are known) on each image of the overall test field are detected and the approximate exterior orientation parameters are computed. Then, the remaining target points are measured using the approximate image locations, determined using these parameters and the 3D object point coordinates parameters. Finally, calibration parameters are determined using a self-calibration bundle adjustment technique. The colored targets within the test field are assigned labels corresponding to their color. For the detection of color targets and computation of approximate exterior orientation elements, HSV color space was used together with space resection computation method for all the possible color labels of targets. To test the proposed method, full automatic calibration was carried out using six different digital cameras. The calibration accuracies achieved in object space were within the range 0.006 to 0.030 mm; the accuracies achieved in image space were within the range 0.14 to 0.51 µm.
In this study, a series of laboratory tests on 100‐mm‐diameter high‐density polyethylene (HDPE) 100 PE flexible pipe buried in poorly graded Sile quartz sand with different relative densities are described. The laboratory tests were performed in a 40‐mm‐thick plexiglass fronted test tank that replicated a classical trench section in field conditions. The HDPE flexible pipe was positioned against the glass with its longitudinal axis perpendicular to the glass. This allowed direct observation of the backfill–pipe interactions. Three high‐definition photogrammetric cameras were used to capture the photogrammetric images through the glass allowing the discrete measurement and image processing of the deformation patterns of the pipe conduit during the pipe installation and incremental surcharge loading. Vertical loads were applied in increments of 10–150 kPa using air pressure membranes. Electric resistant strain gauges measured the bending moments of the pipe walls under vertical surcharge loadings. For each loading step, the vertical deformation of the pipe crown was also measured using linear position transducers. According to the test results, it is understood that the installation technique and backfill relative density have an important effect on circumferential strains, performance, and deformation characteristics of HDPE pipes. It was also observed that close‐range image processing is a very simple and appropriate method for measuring three‐dimensional pipe deformations under various conditions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.