The framework proposed in paper: Barath, Daniel, et al. Making Affine Correspondences Work in Camera Geometry Computation. ECCV 2020
.
It is available at https://arxiv.org/pdf/1906.02290
To build and install only the C++ implementation of the framework, clone or download this repository and then build the project by CMAKE.
$ git clone --recursive https://github.com/danini/affine-correspondences-for-camera-geometry.git
$ cd build
$ cmake ..
$ make
The framework contains a Python binding and Jupyter Notebook examples. To compile with Python the following should be done.
python3 ./setup.py install
or
pip3 install -e .
To build the sample project showing examples of fundamental matrix, homography and essential matrix fitting, set variable CREATE_SAMPLE_PROJECT = ON
when creating the project in CMAKE.
Then
$ cd build
$ ./SampleProject
The example for homography fitting is available at: link.
The example for fundamental matrix fitting is available at: link.
The example for essential matrix fitting is available at: link.
- Eigen 3.0 or higher
- CMake 2.8.12 or higher
- OpenCV 3.0 or higher
- A modern compiler with C++17 support
When using the algorithm, please cite Barath, Daniel, et al. "Making Affine Correspondences Work in Camera Geometry Computation". Proceedings of the IEEE European Conference on Computer Vision. 2020
.
If you use it with Graph-Cut RANSAC, please cite Barath, Daniel, and Matas, Jiří. "Graph-cut RANSAC." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2018
.