首页> 外文期刊>IEEE Transactions on Pattern Analysis and Machine Intelligence >Self-calibration of a 1D projective camera and its application to the self-calibration of a 2D projective camera
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Self-calibration of a 1D projective camera and its application to the self-calibration of a 2D projective camera

机译:一维投影相机的自校准及其在二维投影相机的自校准中的应用

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We introduce the concept of self-calibration of a 1D projective camera from point correspondences, and describe a method for uniquely determining the two internal parameters of a 1D camera, based on the trifocal tensor of three 1D images. The method requires the estimation of the trifocal tensor which can be achieved linearly with no approximation unlike the trifocal tensor of 2D images and solving for the roots of a cubic polynomial in one variable. Interestingly enough, we prove that a 2D camera undergoing planar motion reduces to a 1D camera. From this observation, we deduce a new method for self-calibrating a 2D camera using planar motions. Both the self-calibration method for a 1D camera and its applications for 2D camera calibration are demonstrated on real image sequences.
机译:我们介绍了从点对应关系对一维投影相机进行自我校准的概念,并描述了一种基于三个一维图像的三焦点张量来唯一确定一维相机的两个内部参数的方法。该方法需要估计三焦点张量,该估计可以线性地实现而无需近似,这与2D图像的三焦点张量不同,并且可以在一个变量中求解三次多项式的根。有趣的是,我们证明了经历平面运动的2D摄像机会减少为1D摄像机。从这一观察中,我们得出了一种使用平面运动自校准2D摄像机的新方法。一维相机的自校准方法及其在二维相机校准中的应用均在真实图像序列上进行了演示。

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