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Modeling and calibration of video cameras

机译:摄像机的建模与校准

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摘要

To exploit the accuracy potential of a video camera, all systematic errors must be modeled and compensated for. In this article, a new geometric camera model, where difference in scale and lack of orthogonality between the image axes is compensated for after, and separately from lens distortion, is proposed. The new model can be calibrated from both planar and non-planar calibration objects. The feasibility of the model is demonstrated in a typical camera calibration experiment, which indicates that the new model is more accurate than the traditional one. It also gives a simple solution to the problem of computing undistorted image coordinates from distorted ones. Further, the article suggests how to get initial estimates for all the camera model parameters, how to select the number of parameters modeling lens distortion, and how to reduce the dimension of the search space in the nonlinear optimization. There is also a discussion on the use of analytical partial derivatives.
机译:为了利用摄像机的精度潜力,必须为所有系统错误进行建模和补偿。在本文中,提出了一种新的几何相机模型,其中提出了一种新的几何相机模型,其中在图像轴之间的差异和缺乏正交性之后,并且是在之后,并且与镜头失真分开补偿。可以从平面和非平面校准对象校准新模型。模型的可行性在典型的相机校准实验中展示,这表明新模型比传统更准确。它还给出了从扭曲的图像计算未失真图像坐标的问题的简单解决方案。此外,文章表明如何为所有相机型号参数获得初始估计,如何选择建模镜头失真的参数数量,以及如何降低非线性优化中搜索空间的维度。还有关于使用分析部分衍生物的讨论。

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