Recently, the term smartphone photogrammetry gained popularity. This suggests that photogrammetry may become a simple measurement tool by virtually every smartphone user. The research was undertaken to clarify whether it is appropriate to use the Structure from Motion—Multi Stereo View (SfM-MVS) procedure with self-calibration as it is done in Uncrewed Aerial Vehicle photogrammetry. First, the geometric stability of smartphone cameras was tested. Fourteen smartphones were calibrated on the checkerboard test field. The process was repeated multiple times. These observations were found: (1) most smartphone cameras have lower stability of the internal orientation parameters than a Digital Single-Lens Reflex (DSLR) camera, and (2) the principal distance and position of the principal point are constantly changing. Then, based on images from two selected smartphones, 3D models of a small sculpture were developed. The SfM-MVS method was used, with self-calibration and pre-calibration variants. By comparing the resultant models with the reference DSLR-created model it was shown that introducing calibration obtained in the test field instead of self-calibration improves the geometry of 3D models. In particular, deformations of local concavities and convexities decreased. In conclusion, there is real potential in smartphone photogrammetry, but it also has its limits.
For photogrammetric works, a fundamental issue is the determination of camera internal orientation parameters (IOP). Without camera calibration, it is difficult to imagine a correct adjustment of the image network. Many industries use non-metric cameras, ranging from automatics and robotics, to heritage inventories, and the increasingly popular social mapping phenomenon uses low-budget cameras. Many different calibration methods exist, but dedicated calibration fields are commonly replaced by fast in-plane calibration with regular patterns. The main goal of this research is to verify the thesis that calibrating cameras on a checkerboard gives worse results in determining IOP than on a laboratory test field which may translate into the resulting model. For the purpose of this study, a special field was constructed, allowing calibration of the instruments on the basis of the network solution by the bundle adjustment. Unlike classical 2D fields, the field is equipped with a cork background providing a good base for matching and automatically detecting measurement marks. Calibration results were compared with calibration performed on a checkerboard implemented in MATLAB Camera Calibration Toolbox. In order to determine IOP in MATLAB, images of the checkerboard must be taken in such a way, that the whole pattern fits into the frame, otherwise toolbox defines the incorrectly coordinate system, which has a bad impact on calibration results. Moreover, the determined parameters have several times larger standard deviations than those determined in the laboratory test field, which confirms the thesis.
<p>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; With the technological progress, the demand for a three-dimensional presentation of the world around us is growing. Currently, modelling of urban space in 3d based on presenting it as simple geometric solids is not able to satisfy the needs of the constantly growing market. There are also noticeable trends aimed at representing the real world as faithfully as possible in virtual space.</p><p>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; The purpose of this work is to show the differences between the individual levels of detail (LoD) of the building facade model obtained using classic geodetic measurements as well as ground photogrammetry and UAV photogrammetry. For this purpose, pictures of the building facade were taken and its characteristic elements were measured so that the generated model was metric.</p><p>&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; Creating a vector model of the facade consisted in modelling individual blocks based on points obtained from the total station measurement. The model was generalized for individual levels of detail using fewer points to make it. Subsequently, vector models were textured by photos.</p><p>In addition, oblique facade photos were developed, and then a triangular mesh model was made from the dense point cloud generated on their basis. The model was analyzed for meeting the accuracy criteria of individual LoDs in order to determine whether the use of only photogrammetric data allows the generation of a suitably detailed spatial model.</p><p>The resulting models were compared with each other, thanks to which it is possible to verify whether the facade is symmetrical and how repeatable its architectural elements are. The outcome also enables the assessment of the accuracy with which the building elements should be measured in order to obtain a reliable model that meets the criteria of the assumed LoD level for the resulting product.</p>
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.