Open AccessCalibration and orientation of industrial online photogrammetry systems in situ
Author(s) -
Sun Peng,
Lu Naiguang,
Dong Mingli,
Wang Jun,
Yan Bixi
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.9202
Subject(s) - bundle adjustment , photogrammetry , orientation (vector space) , calibration , computer science , bar (unit) , length measurement , bundle , scale (ratio) , point (geometry) , computation , volume (thermodynamics) , computer vision , accuracy and precision , camera resectioning , block (permutation group theory) , artificial intelligence , algorithm , mathematics , optics , geometry , physics , materials science , statistics , quantum mechanics , composite material , meteorology
This study proposes an analytical method for calibrating and orienting online photogrammetric systems using a scale bar. The primary idea is building control lengths in the measurement volume by moving and rotating the scale bar and then conducting a self‐calibration bundle adjustment using images of the control lengths. In this study, the five‐point relative orientation method is used to provide estimations of the exterior camera parameters. Additionally, this study elaborates the model of the lengths constrained self‐calibration bundle adjustment, the block computation algorithm and the accuracy assessment. This method obtains both the interior and the exterior orientation parameters of the two cameras, and provides spatial bar length reconstruction precision as the performance evaluation. Simulations are conducted to analyze the calibration accuracy and the results show that the method achieves comparable accuracy and precision against the state‐of‐the‐art method. However, the method does not need steady and well distributed 3D points and is easy to operate. Real data experimental results show that the maximum length measurement error of this method in a volume of 5 m × 4 m × 2 m is <0.4 mm.