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Towards complete generic camera calibration

机译:全面完成通用相机校准

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We consider the problem of calibrating a highly generic imaging model, that consists of a non-parametric association of a projection ray in 3D to every pixel in an image. Previous calibration approaches for this model do not seem to be directly applicable for cameras with large fields of view and non-central cameras. In this paper, we describe a complete calibration approach that should in principle be able to handle any camera that can be described by the generic imaging model. Initial calibration is performed using multiple-images of overlapping calibration grids simultaneously. This is then improved using pose estimation and bundle adjustment-type algorithms. The approach has been applied on a wide variety of central and non-central cameras including fisheye lens, catadioptric cameras with spherical and hyperbolic mirrors, and multi-camera setups. We also consider the question if non-central models are more appropriate for certain cameras than central models.
机译:我们考虑了校准高度通用的成像模型的问题,该模型包括3D投影射线与图像中每个像素的非参数关联。该模型的先前校准方法似乎不适用于具有大视野的相机和非中央相机。在本文中,我们描述了一种完整的校准方法,该方法原则上应能够处理可以由通用成像模型描述的任何相机。初始校准是同时使用重叠校准网格的多个图像执行的。然后使用姿势估计和束调整类型算法对此进行改进。该方法已应用于各种中央和非中央相机,包括鱼眼镜头,带球面和双曲面镜的折反射相机以及多相机设置。我们还考虑以下问题:非中央模型是否比中央模型更适合某些相机。

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