基于运动结构图的无人机序列影像三维重建

无人机序列影像具有重叠度高、拓扑联系强的特点。针对现有增量式三维重建算法在处理大规模无人机影像时效率低、输出不稳定的问题，提出基于运动结构图的无人机序列影像三维重建方法。顾及地理位置信息与IMU(Inertial measurement unit) 数据建立图像索引集，提高图像匹配效率，并使用随机抽样一致性算法计算相对运动；使用运动结构图表示影像之间的“ 关联”，采用闭环检测剔除错误边；借助李代数与李群的映射关系， 融合1 L 范式与M 估计一次性求解影像全局运动，期间只进行一次光束法平差，降低了计算复杂度。实验验证本文方法在效率和效果上得到了提高。

3D Reconstruction of UAV Sequence Image Based on Motion Structure Graph

UAV sequence image has the characteristics of high overlap and strong topological connection. Aiming at the inefficient and unstable in processing the large-scale UAV images of the existing incremental 3D reconstruction algorithm, a 3D reconstruction method based on motion structure graph is proposed. The image matching index is established by using the geolocation information and IMU data to improve the image matching efficiency, and the random motion consistency algorithm is used to calculate the relative motion; motion structure graph is used to represent the "association" between images, and closed-loop detection algorithm is used to eliminate the false edges. Under the mapping relationship between Lie algebra and Lie group, the global motion of the image is solved at one time by 1 L paradigm and M estimation, and the beam adjustment is used only once. Experiments show that the proposed algorithm improves the efficiency and reconstruction result.