基于遗传算法的射影重构

在实现分层重构的过程中，射影重构是关键的第1步。目前，大多已有算法对模拟数值是非常有效的，但对于真实图象效果并不理想。为了寻求更为鲁棒的算法，提出了一种基于遗传算法的射影重构算法。该算法对于射影深度采用十进制编码，并以测量矩阵的秩为4作为约束，来定义适应度函数，然后利用遗传算法，并结合奇异值分解（SVD）技术来迭代估计射影深度，进而实现射影重构，该算法是行之有效的，且鲁棒性较好。

The Projective Reconstruction Based on Genetic Algorithms

In computer vision, it is called multi views 3D reconstruction for recovering both camera and object shapes from multiple images, and it is currently a topic of lively interest. A hierarchical reconstruction method had introduced in 1996. In the course of completing the hierarchical reconstruction, the projective reconstruction is the first key step, having very important effect on the precision of euclidean reconstruction. The existence methods are very efficient for simulation data, but they are not perfect for real image. Namely, they are not robust and the reliable results can only be obtained if images match accurately. In this paper, the projective reconstruction based on genetic algorithms is proposed, the projective depths are coded by using decimal system and the adaptability function is defined by a constraint of the measurement matrix rank 4. The projective depths are iteratively estimated by genetic algorithms and Singular value decomposition (SVD) so that the measurement matrix is made to be as close as possible to rank 4, and then the projective reconstruction is realized. The validity and robusticity of the proposed algorithm is confirmed by experiments.