/aerial_mapper

Real-time Dense Point Cloud, Digital Surface Map (DSM) and (Ortho-)Mosaic Generation for UAVs

Primary LanguageC++BSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

aerial-mapper

Overview

  • Load camera poses from different formats (such as PIX4D, COLMAP)
  • Generates a dense point cloud from raw images, camera poses and camera intrinsics
  • Generates Digital Surface Models (DSMs) from raw point clouds and exports e.g. to GeoTiff format
  • Different methods to generate (ortho-)mosaics from raw images, camera poses and camera intrinsics

Package Overview

Getting started

Output samples

Dense point cloud
(from virtual stereo pair, 2 images)
Digital Surface Map
(DSM, exported as GeoTiff)
(Ortho-)Mosaic
(from homography, 249 images)
Raw images Dense point cloud Digital Surface Map
Observation Angle
(red: nadir)
Grid-based Orthomosaic
(Cell resolution: 0.5m)
Textured DSM

Publications

If you use this work in an academic context, please cite the following publication:

T. Hinzmann, J. L. Schönberger, M. Pollefeys, and R. Siegwart, "Mapping on the Fly: Real-time 3D Dense Reconstruction, Digital Surface Map and Incremental Orthomosaic Generation for Unmanned Aerial Vehicles" [PDF]

@INPROCEEDINGS{fsr_hinzmann_2017,
   Author = {T. Hinzmann, J. L. Schönberger, M. Pollefeys, and R. Siegwart},
   Title = {Mapping on the Fly: Real-time 3D Dense Reconstruction, Digital Surface Map and Incremental Orthomosaic Generation for Unmanned Aerial Vehicles},
   Booktitle = {Field and Service Robotics - Results of the 11th International Conference},
   Year = {2017}
}

Acknowledgment

This work was partially funded by the European FP7 project SHERPA (FP7-600958) and the Federal office armasuisse Science and Technology under project number 050-45. Furthermore, the authors wish to thank Lucas P. Teixeira from the Vision for Robotics Lab at ETH Zurich for sharing scripts that bridge the gap between Blender and Gazebo.