利用三视匹配元进行多视影像批处理重建

A Batch Reconstruction Algorithm of Multi-view Images Using Image Triplets

  • 摘要: 无序多视影像的三维重建对噪声非常敏感,错误的匹配关系会影响重建的精度,甚至直接导致重建失败。提出了一种稳健的批处理重建算法,首先利用回路闭合约束剔除可能存在误匹配的三视匹配元,然后以三视匹配元中的三焦张量约束代替传统算法的核线约束来计算所有影像旋转矩阵和相机中心位置的全局最优解。重建过程中引入高效的并查集算法来提取多视匹配点,并利用迭代线性三角形算法计算空间点的三维坐标。实验结果表明,所提算法在重建效率和计算精度方面都能取得较好的结果。

     

    Abstract: 3D reconstruction of unordered multi-view images is very sensitive to noise. Error matching relations will affect the accuracy of the reconstruction or even lead to failure. A robust batch reconstruction algorithm is proposed in this paper, first the triplets which may contain mismatches are removed using closed cycle constraint, and then the trifocal tensor constraint in triplet is used instead of the epipolar constraint of the traditional algorithm, also the linear programming algorithm with the l norm is used instead of the second order cone programming to calculate a global optimum of rotations and locations of all the images. An efficient Union Find algorithm is introduced into the reconstruction to exact the multi-view matching points, and the 3D points are computed using the iterative linear triangulation. Experimental results show that the proposed method performs satisfactorily in terms of reconstruction efficiency and accuracy.

     

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