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A Generic Multi-Projection-Center Model and Calibration Method for Light Field Cameras

机译:光场相机的通用多投影中心模型和标定方法

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Light field cameras can capture both spatial and angular information of light rays, enabling 3D reconstruction by a single exposure. The geometry of 3D reconstruction is affected by intrinsic parameters of a light field camera significantly. In the paper, we propose a multi-projection-center (MPC) model with 6 intrinsic parameters to characterize light field cameras based on traditional two-parallel-plane (TPP) representation. The MPC model can generally parameterize light field in different imaging formations, including conventional and focused light field cameras. By the constraints of 4D ray and 3D geometry, a 3D projective transformation is deduced to describe the relationship between geometric structure and the MPC coordinates. Based on the MPC model and projective transformation, we propose a calibration algorithm to verify our light field camera model. Our calibration method includes a close-form solution and a non-linear optimization by minimizing re-projection errors. Experimental results on both simulated and real scene data have verified the performance of our algorithm.
机译:光场相机可以捕获光线的空间和角度信息,从而可以通过一次曝光进行3D重建。 3D重建的几何形状受光场相机的固有参数的影响很大。在本文中,我们提出了一个具有6个内在参数的多投影中心(MPC)模型,以基于传统的两平行平面(TPP)表示来表征光场相机。 MPC模型通常可以参数化不同成像形式的光场,包括常规和聚焦光场相机。通过4D射线和3D几何的约束,推导了3D投影变换来描述几何结构和MPC坐标之间的关系。基于MPC模型和投影变换,我们提出了一种校准算法来验证我们的光场相机模型。我们的校准方法包括闭合形式的解决方案和通过最小化重投影误差进行的非线性优化。在模拟和真实场景数据上的实验结果证明了我们算法的性能。

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