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This is an open-source implementation of paper: Real-time Incremental UAV Image Mosaicing based on Monocular SLAM.

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Map2DFusion


Brief Introduction

This is an open-source implementation of paper: Map2DFusion: Real-time Incremental UAV Image Mosaicing based on Monocular SLAM.

Website : http://zhaoyong.adv-ci.com/map2dfusion/

Video : https://www.youtube.com/watch?v=-kSTDvGZ-YQ

PDF : http://zhaoyong.adv-ci.com/Data/map2dfusion/map2dfusion.pdf

1. Compilation

1.1. Resources

  • Download the latest code with:
    • Git:

        git clone https://github.com/zdzhaoyong/Map2DFusion
      

1.2. Dependencies

  • OpenCV : sudo apt-get install libopencv-dev
  • Qt : sudo apt-get install build-essential g++ libqt4-core libqt4-dev libqt4-gui qt4-doc qt4-designer
  • QGLViewer : sudo apt-get install libqglviewer-dev libqglviewer2
  • Boost : sudo apt-get install libboost1.54-all-dev
  • GLEW : sudo apt-get install libglew-dev libglew1.10
  • GLUT : sudo apt-get install freeglut3 freeglut3-dev
  • CUDA (optional) : see https://developer.nvidia.com/cuda-downloads

Warnning: Compilation with CUDA can be enabled after CUDA_PATH defined.

1.3. Compilation

If you are using linux systems, it can be compiled with one command (tested on ubuntu 14.04):

cd Map2DFusion;make

2. Usage

Obtain the sample sequence and launch:

git clone https://github.com/zdzhaoyong/phantom3-village-kfs
./Map2DFusion DataPath=phantom3-village-kfs

More sequences can be downloaded at the NPU DroneMap Dataset.

3. Contact

If you have any issue compiling/running Map2DFusion or you would like to know anything about the code, please contact the authors:

 Yong Zhao -> [email protected]

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This is an open-source implementation of paper: Real-time Incremental UAV Image Mosaicing based on Monocular SLAM.

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  • C++ 80.0%
  • C 13.2%
  • HTML 5.6%
  • Cuda 0.5%
  • CMake 0.3%
  • QMake 0.1%
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