3D Curves Reconstruction from Multiple Images

F. Mai, Y. Hung
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引用次数: 8

Abstract

In this paper, we propose a new approach for reconstructing 3D curves from a sequence of 2D images taken by uncalibrated cameras. A curve in 3D space is represented by a sequence of 3D points sampled along the curve, and the 3D points are reconstructed by minimizing the distances from their projections to the measured 2D curves on different images (i.e., 2D curve reprojection error). The minimization problem is solved by an iterative algorithm which is guaranteed to converge to a (local) minimum of the 2D reprojection error. Without requiring calibrated cameras or additional point features, our method can reconstruct multiple 3D curves simultaneously from multiple images and it readily handles images with missing and/or partially occluded curves.
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从多个图像重建3D曲线
在本文中,我们提出了一种新的方法来重建三维曲线从一系列的二维图像由未校准的相机。三维空间中的曲线由沿着曲线采样的一系列三维点表示,通过最小化其投影到不同图像上测量的二维曲线的距离(即二维曲线重投影误差)来重建三维点。最小化问题采用迭代算法求解,保证收敛到二维重投影误差的(局部)最小值。不需要校准相机或额外的点特征,我们的方法可以从多个图像同时重建多个3D曲线,并且它很容易处理丢失和/或部分遮挡曲线的图像。
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