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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >Revisiting Zhang's 1D calibration algorithm
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Revisiting Zhang's 1D calibration algorithm

机译：回顾张的一维校准算法

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摘要

In recent years, the camera calibration using 1D patterns has been studied and improved by researchers all over the world. However, the progress in that area has been mainly in the sense of reducing the restrictions to the 1D pattern movement. On the other hand, the method's accuracy still demands improvements. In the present paper, the original technique proposed by Zhang is revisited and we demonstrate that the method's accuracy can be significantly improved, simply by analyzing and reformulating the problem. The numerical conditioning can be improved if a simple data normalization is performed. Furthermore, a non-linear solution based on the Partitioned Levenberg-Marquardt algorithm is proposed. That solution takes advantage of the problem's particular structure to reduce the computational complexity of the original method and to improve the accuracy. Tests using both synthetic and real images demonstrate that the calibration method using 1D patterns can be applied in practice, with accuracy comparable to other already traditional methods.
机译：近年来，全世界的研究人员已经研究并改进了使用1D模式进行相机校准的方法。然而，该领域的进展主要是在减少对一维图案移动的限制的意义上。另一方面，该方法的准确性仍需要改进。在本文中，对Zhang提出的原始技术进行了重新研究，我们证明了该方法的准确性可以通过简单地分析和重新构造问题来显着提高。如果执行简单的数据归一化，则可以改善数值条件。此外，提出了一种基于分区Levenberg-Marquardt算法的非线性解决方案。该解决方案利用问题的特殊结构来减少原始方法的计算复杂度并提高准确性。使用合成图像和真实图像进行的测试表明，使用一维模式的校准方法可以在实践中应用，其准确性可与其他已经采用传统方法的方法相媲美。

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