一种基于无人机序列成像的地形地貌重建方法

A 3D Landform Reconstruction Method Based on UAV Image Sequences

以无人机平台上普通摄像机获取的序列图像为对象,提出了一种对地三维重建的自动化处理方法。首先提出了基于视差分析的序列图像关键帧选择方法,对关键帧图像特征点进行鲁棒性的提取与匹配;第二步用加权的RANSAC算法估计基础矩阵,同时获取准确匹配的内点集。根据已标定的像机内参数,解算相对运动并进行优化。最后对待重建的目标点提出几何约束和单应约束融合的方法实现快速准确匹配,通过三角交会完成目标形貌三维重建。仿真实验结果表明该算法对序列图像具有较好的自动化程度和鲁棒性。

To generate 3D information from the image sequence of the normal UAV（Unmanned Aerial Vehicle） loading camera,a reconstruction method is proposed. At the first step, the key frame selecting from the sequence ,the robust features extracting and corresponding of multi-images of sequence are accomplished. At the second step, two views which are far away enough and sharing lots of correspondences are selected. With the correspondences the RANSAC algorithm estimates the fundamental matrix robust and then the more accurate correspondences with less outliers are gotten, which are called as inliers. Basing on the calibrated camera parameters, the motions R and T of the view is computed by decomposition of the fundamental matrix,and then it is optimized with the correct correspondences. At last, 3D reconstruction is realized by the method of triangle communicating. Experiment results show that the algorithm is efficient and it improves the robustness and accuracy of the reconstruction.