Evaluation of the Quality of a Checkerboard Camera Calibration Compared to a Calibration on a Laboratory Test Field

A. Jasińska
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Abstract

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.
棋盘摄像机标定与实验室标定的质量评价
在摄影测量工作中,相机内部定向参数(IOP)的确定是一个基本问题。没有摄像机的校准,很难想象图像网络的正确调整。许多行业都使用非公制相机,从自动化和机器人到遗产清单,越来越流行的社交地图现象使用低成本相机。存在许多不同的校准方法,但专用校准域通常被具有规则模式的快速平面内校准所取代。本研究的主要目的是验证在棋盘上校准相机在确定IOP方面的结果比在实验室测试场差,这可能会转化为结果模型。为了本研究的目的,构建了一个特殊的领域,允许通过束平差在网络解决方案的基础上对仪器进行校准。与传统的2D油田不同,该油田配备了软木背景,为匹配和自动检测测量标记提供了良好的基础。将标定结果与在MATLAB摄像机标定工具箱中实现的棋盘上进行的标定进行了比较。为了在MATLAB中确定IOP,必须将棋盘的图像拍摄成整个图案与框架相匹配的方式,否则工具箱定义的坐标系不正确,会对校准结果产生不良影响。此外,所确定的参数的标准偏差比实验室测试现场确定的参数大几倍,这证实了本文的观点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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