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A case against Kruppa's equations for camera self-calibration

机译:反对Kruppa相机自校准方程式的案例

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We consider the self-calibration problem for perspective cameras and especially the classical Kruppa equation approach. It is known that for several common types of camera motion, self-calibration is degenerate, which manifests itself through the existence of ambiguous solutions. The author previously (1997, 1999) studied these critical motion sequences and showed their importance for practical applications. Here, we reveal a type of camera motion that is not critical for the generic self-calibration problem, but for which the Kruppa equation approach fails. This is the case if the optical centers of all cameras lie on a sphere and if the optical axes pass through the sphere's center, a very natural situation for 3D object modeling from images. Results of simulated experiments demonstrate the instability of numerical self-calibration algorithms in near-degenerate configurations.
机译:我们考虑了透视相机的自校准问题,尤其是经典的Kruppa方程法。众所周知,对于几种常见的摄像机运动类型,自校准会退化,这通过模棱两可的解决方案的存在来体现出来。作者先前(1997,1999)研究了这些临界运动序列,并显示了它们在实际应用中的重要性。在这里,我们揭示了一种相机运动类型,它对于一般的自校准问题不是很关键,但是对于Kruppa方程方法却失败了。如果所有摄像机的光学中心都位于球体上,并且光轴穿过球体的中心,则情况非常自然,这是从图像进行3D对象建模的自然情况。模拟实验的结果表明,在简并的配置中,数值自校准算法的不稳定性。

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