Camera calibration with one-dimensional objects
Camera calibration with one-dimensional objects
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DOI：
10.1109/tpami.2004.21
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发表时间：
2004-07-01
影响因子：
23.6
通讯作者：
Zhang, ZY
中科院分区：
文献类型：
--
作者：
Zhang, ZY
相机标定在计算机视觉和摄影测量领域已被广泛研究，文献中提出的技术包括使用3D装置（彼此正交的两个或三个平面，或进行纯平移的平面等）、2D物体（进行未知运动的平面图案）以及0D特征（使用未知场景点的自标定）。然而，本文提出了一种使用1D物体（排列在一条直线上的点）的新标定技术，从而填补了标定中缺失的维度。特别是，我们表明使用自由移动的1D物体无法进行相机标定，但如果有一个点是固定的则可以解决。如果对这样的1D物体进行六次或更多次观测，就可以得出一个闭式解。为了获得更高的精度，随后使用基于最大似然准则的非线性技术来优化估计。还对奇点进行了研究。除了理论方面，所提出的技术在实践中也很重要，特别是在标定相互分开安装的多个相机时，此时要求标定物体能同时被看到。
Camera calibration has been studied extensively in computer vision and photogrammetry and the proposed techniques in the literature include those using 3D apparatus (two or three planes orthogonal to each other or a plane undergoing a pure translation, etc.), 2D objects (planar patterns undergoing unknown motions), and 0D features (self-calibration using unknown scene points). Yet, this paper proposes a new calibration technique using 1D objects (points aligned on a line), thus filling the missing dimension in calibration. In particular, we show that camera calibration is not possible with free-moving 1D objects, but can be solved if one point is fixed. A closed-form solution is developed if six or more observations of such a 1D object are made. For higher accuracy, a nonlinear technique based on the maximum likelihood criterion is then used to refine the estimate. Singularities have also been studied. Besides the theoretical aspect, the proposed technique is also important in practice especially when calibrating multiple cameras mounted apart from each other, where the calibration objects are required to be visible simultaneously.