Creating 3D models with uncalibrated cameras

Mei Han, T. Kanade
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引用次数: 60

Abstract

We describe a factorization-based method to recover 3D models from multiple perspective views with uncalibrated cameras. The method first performs a projective reconstruction using a bilinear factorization algorithm, and then converts the projective solution to a Euclidean one by enforcing metric constraints. We present three factorization-based normalization algorithms to generate the Euclidean reconstruction and the intrinsic parameters, assuming zero skews. The first two algorithms are linear, one for dealing with the case that only the focal lengths are unknown, and another for the case that the focal lengths and the constant principal point are unknown. The third algorithm is bilinear dealing with the case that the focal lengths, the principal points and the aspect ratios are all unknown. We present the results of applying this method to building modeling, terrain recovery and multi-camera calibration.
使用未校准的相机创建3D模型
我们描述了一种基于因子分解的方法,用于从未校准的相机的多视角视图中恢复3D模型。该方法首先使用双线性分解算法进行投影重建,然后通过强制度量约束将投影解转换为欧几里德解。我们提出了三种基于因式分解的归一化算法来生成欧几里得重构和固有参数,假设偏差为零。前两种算法是线性的,一种用于处理焦距未知的情况,另一种用于焦距和恒定主点未知的情况。第三种算法是双线性算法,用于处理焦距、主点和长宽比都未知的情况。给出了该方法在建筑物建模、地形恢复和多摄像机标定等方面的应用结果。
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