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首页> 外文会议>International Conference on Computational Science and Its Applications(ICCSA 2004) pt.4; 20040514-20040517; Assisi; IT >Initialization Method for the Self-Calibration Using Minimal Two Images
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Initialization Method for the Self-Calibration Using Minimal Two Images

机译：最少两张图像进行自校准的初始化方法

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摘要

Recently, 3D structure recovery through self-calibration of camera has been actively researched. Traditional calibration algorithm requires known 3D coordinates of the control points while self-calibration only requires the corresponding points of images, thus it has more flexibility in real application. In general, self-calibration algorithm results in the nonlinear optimization problem using constraints from the intrinsic parameters of the camera. Thus, it requires initial value for the nonlinear minimization. Traditional approaches get the initial values assuming they have the same intrinsic parameters while they are dealing with the situation where the intrinsic parameters of the camera may change. In this paper, we propose new initialization method using the minimum 2 images. Proposed method is based on the assumption that the least violation of the camera's intrinsic parameter gives more stable initial value. Synthetic and real experiment shows this result.
机译：近来，已经积极地研究了通过照相机的自校准进行的3D结构恢复。传统的标定算法需要控制点的已知3D坐标，而自标定只需要图像的相应点，因此在实际应用中具有更大的灵活性。通常，自校准算法会使用来自相机固有参数的约束来导致非线性优化问题。因此，它需要用于非线性最小化的初始值。假设传统方法在处理相机的固有参数可能发生变化的情况时具有相同的固有参数，则会获得初始值。在本文中，我们提出了使用最少2张图像的新初始化方法。提出的方法基于以下假设：对相机固有参数的最小违反会给出更稳定的初始值。综合和真实的实验表明了这一结果。

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