Map2DFusion: Real-time incremental UAV image mosaicing based on monocular SLAM
Shuhui Bu, Yong Zhao, Gang Wan, Zhenbao Liu
Abstract
In this paper we present a real-time approach to stitch large-scale aerial images incrementally. A monocular SLAM system is used to estimate camera position and attitude, and meanwhile 3D point cloud map is generated. When GPS information is available, the estimated trajectory is transformed to WGS84 coordinates after time synchronized automatically. Therefore, the output orthoimage retains global coordinates without ground control points. The final image is fused and visualized instantaneously with a proposed adaptive weighted multiband algorithm. To evaluate the effectiveness of the proposed method, we create a publicly available aerial image dataset with sequences of different environments. The experimental results demonstrate that our system is able to achieve high efficiency and quality compared to state-of-the-art methods. In addition, we share the code on the website with detailed introduction and results.
BibTeX
@inproceedings{iros2016_map2dfusionrealt,
title = {Map2DFusion: Real-time incremental UAV image mosaicing based on monocular SLAM},
author = {Shuhui Bu and Yong Zhao and Gang Wan and Zhenbao Liu},
booktitle = {IROS 2016},
year = {2016}
}