EPnP: An Accurate O(n) Solution to the PnP Problem
EPnP: An Accurate O(n) Solution to the PnP Problem
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DOI：
10.1007/s11263-008-0152-6
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发表时间：
2009-02-01
影响因子：
19.5
通讯作者：
Fua, Pascal
中科院分区：
文献类型：
--
作者：
Lepetit, Vincent;Moreno-Noguer, Francesc;Fua, Pascal
我们提出了一个非迭代的解决方案的Pestival问题的估计的姿态校准摄像机从n个3D到2D点对应关系，其计算复杂度与n线性增长。这与最先进的方法相反，这些方法是O（n（5））甚至O（n（8）），而不是更准确。我们的方法是适用于所有na每千日元4的部分，并妥善处理平面和非平面配置。我们的中心思想是将n个3D点表示为四个虚拟控制点的加权和。然后，问题简化为估计相机参考中这些控制点的坐标，这可以在O（n）时间内完成，通过将这些坐标表示为12 x12矩阵的特征向量的加权和，并求解少量常数的二次方程来选择正确的权重。此外，如果需要最大精度，则可以使用闭合形式解的输出来初始化高斯-牛顿方案，这在可以忽略的额外时间量的情况下提高了精度。我们的方法的优点是通过全面的测试合成和真实的数据。
We propose a non-iterative solution to the PnP problem-the estimation of the pose of a calibrated camera from n 3D-to-2D point correspondences-whose computational complexity grows linearly with n. This is in contrast to state-of-the-art methods that are O(n (5)) or even O(n (8)), without being more accurate. Our method is applicable for all na parts per thousand yen4 and handles properly both planar and non-planar configurations. Our central idea is to express the n 3D points as a weighted sum of four virtual control points. The problem then reduces to estimating the coordinates of these control points in the camera referential, which can be done in O(n) time by expressing these coordinates as weighted sum of the eigenvectors of a 12x12 matrix and solving a small constant number of quadratic equations to pick the right weights. Furthermore, if maximal precision is required, the output of the closed-form solution can be used to initialize a Gauss-Newton scheme, which improves accuracy with negligible amount of additional time. The advantages of our method are demonstrated by thorough testing on both synthetic and real-data.