Abstract
Close range photogrammetry (CRP) has gained increasing relevance over the years with its principles and theories being applied in diverse applications. Further supporting this trend, the current increase in the wide spread usage of mobile phones with high resolution cameras is expected to further popularize positioning by CRP. This paper presents the results of an experimental study wherein two (2) non-metric mobile phone cameras have been used to determine the 3-D coordinates of points on a building by using the collinearity condition equation in an iterative least square bundle adjustment process in MATLAB software environment. The two (2) mobile phones used were Tecno W3 and Infinix X509 phones with focal lengths of 5.432 mm and 8.391 mm respectively. Statistical tests on the results obtained shows that there is no significant difference between the 3-D coordinates obtained by ground survey and those obtained from both cameras at 99% confidence level. Furthermore, the study confirmed the capability of non-metric mobile phone cameras to determine 3D point positions to centimeter level accuracy (with maximum residuals of 11.8 cm, 31.0 cm, and 5.9 cm for the Tecno W3 camera and 14.6 cm, 16.1 cm and 1.8 cm for the Infinix X509 camera in the Eastings, Northings and Heights respectively).
Highlights
Close-range photogrammetry (CRP) has found many diverse applications in the fields of industry, biomechanics, chemistry, biology, archaeology, architecture, automotive and aerospace, construction as well as accident reconstruction (Jiang et al, 2008)
While both studies justified the capacity of non-metric cameras to be used for photogrammetric tasks, the computational procedure in both studies were plainly analytical with the obtained results depending largely on the stereo-comparator used for the photogrammetric measurement
This study has ascertained the statistical reliability of using non-metric cameras for determination of low order accuracy position via CRP
Summary
Close-range photogrammetry (CRP) has found many diverse applications in the fields of industry, biomechanics, chemistry, biology, archaeology, architecture, automotive and aerospace, construction as well as accident reconstruction (Jiang et al, 2008). Consequent upon its many applications, CRP has witnessed a wide range of developments in the past 4 decades many of which are results of automation and digital techniques which occurred on the sidelines of mainstream photogrammetry (Fraser, 2015). Many of these developments have been especially concerned with models and automation of the procedure for the rigorous determination of the geometric relationship that exist between image and object as at the time of image capture which is the fundamental task of photogrammetry (Mikhail et al, 2001; Luhmann et al, 2006). While both studies justified the capacity of non-metric cameras to be used for photogrammetric tasks, the computational procedure in both studies were plainly analytical with the obtained results depending largely on the stereo-comparator used for the photogrammetric measurement
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