一种基于无人机序列图像的地形地貌三维快速重建方法

提出了一种基于无人机序列图像的地形地貌三维重建方法,该方法采用Harris特征点和SIFT特征向量来提取图像特征,实现图像配准;采用准透视投影模型和因子化方法对未标定的图像序列进行自动标定;通过高效次优解三角化方法获取三维点云坐标;通过准稠密化扩散算法对三维点云进行稠密化;采用捆绑调整算法提高了空间三维点云的精度;采用Possion表面重建方法对三维点云进行了网格化处理.本文为无人机序列图像的应用提供了一个新的思路,拓展了无人机的应用空间.

An Approach to Automatic Great-scene 3D Reconstruction Based on UAV Sequence Images

In this paper, we propose an approach to automatic great-scene 3D reconstruction based on UAV sequence ima- ges. In this method, Harris feature point and SIFT feature vector is used to distill image feature, achieve images matc- hing; quasi--perspective projection model and factorization is employed to calibrate the uncalibrated image sequences auto matically; Efficient suboptimal solutions to the optimal triangulation is plied to obtain the coordinate of 3D points; quasi dense diffusing algorithm is bestowed to make 3D point denseness; bundle adjustment algorithm is betaken to improve the precision of 3D points; Possion surface reconstruction approach is used to make 3D points gridded. This paper introduces the theory and technology of computer vision into great-scene 3D reconstruction, provides a new way for the construction of 3D scene, and provides a new thinking for the appliance of UAV sequence images.