LODM: Large-scale Online Dense Mapping for UAV
Jianxin Huang,Laijian Li,Xiangrui Zhao,Xiaolei Lang,Deye Zhu,Yong Liu,Jianxin Huang,Laijian Li,Xiangrui Zhao,Xiaolei Lang,Deye Zhu,Yong Liu
This paper proposes an online large-scale dense mapping method for UAVs with a height of 150–250 meters. We first fuse the GPS with the visual odometry to estimate the scaled poses and sparse points. In order to use the depth of sparse points for depth map, we propose Sparse Confidence Cascade View-Aggregation MVSNet (SCCVA-MVSNet), which projects the depth-converged points in the sliding window o...