https://github.com/mergarsal/FastCertRelPose

Fast and robust certifiable relative pose estimation
https://github.com/mergarsal/FastCertRelPose

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Fast and robust certifiable relative pose estimation

• Host: GitHub
• URL: https://github.com/mergarsal/FastCertRelPose
• Owner: mergarsal
• License: gpl-3.0
• Created: 2021-01-19T12:37:39.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2023-04-22T11:51:59.000Z (about 1 year ago)
• Last Synced: 2024-02-04T06:09:50.436Z (5 months ago)
• Language: C++
• Size: 128 KB
• Stars: 55
• Watchers: 6
• Forks: 7
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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• Awesome-Self-Driving - FastCertRelPose - Fast and robust certifiable relative pose estimation. (5. Calibration / 3.4. Others)

README

        
# Fast and Robust Relative Pose Estimation for Calibrated Cameras

This repository contains the code 

for the relative pose estimation 

between two central and calibrated cameras 

for the [paper](http://arxiv.org/abs/2101.08524) [1]. 

**Authors:** [Mercedes Garcia-Salguero](http://mapir.uma.es/mapirwebsite/index.php/people/290), [Javier Gonzalez-Jimenez](http://mapir.isa.uma.es/mapirwebsite/index.php/people/95-javier-gonzalez-jimenez)

**License:** [GPLv3](https://raw.githubusercontent.com/mergarsal/FastCertRelPose/main/LICENSE)

If you use this code for your research, please cite:

```

@misc{garciasalguero2021fast,

      title={Fast and Robust Certifiable Estimation of the Relative Pose Between Two Calibrated Cameras}, 

      author={Mercedes Garcia-Salguero and Javier Gonzalez-Jimenez},

      year={2021},

      eprint={2101.08524},

      archivePrefix={arXiv},

      primaryClass={cs.CV}

}

```

Some parts of this repository are based on previous works: 

1. Matlab & python bindings from [TEASER++](https://arxiv.org/pdf/2001.07715.pdf)

        ```

                @article{yang2020teaser,

                  title={Teaser: Fast and certifiable point cloud registration},

                  author={Yang, Heng and Shi, Jingnan and Carlone, Luca},

                  journal={arXiv preprint arXiv:2001.07715},

                  year={2020}

                }

        ```

2. Scene generation from [opengv](https://github.com/laurentkneip/opengv.git) 

## Dependences 

* Eigen 

 ```

        sudo apt install libeigen3-dev

 ```

* Optimization (own fork)

 ```

        git clone https://github.com/mergarsal/Optimization.git

 ```

* GNCSO 

```

        git clone --recursive https://github.com/mergarsal/GNCSO.git 

```

* OpenGV

```

        git clone https://github.com/laurentkneip/opengv.git

```

## Build

```

git clone --recursive https://github.com/mergarsal/FastCertRelPose.git

cd GNCSO

mkdir build & cd build 

cmake .. 

make -jX

```

The compiled examples should be inside the `bin` directory. Run: 

```

        ./bin/example_essential_matrix

```

 

## Install 

In `build` folder: 

```

        sudo make install

```

We also provide the uninstall script: 

```

        sudo make uninstall

```

## How to use the library in your project

See the example in the folder `example_install` 

for the basic elements. 

       

1. In your CMakeLists.txt, add the dependences:

```

        find_package(gncso REQUIRED)

        find_package(opengv REQUIRED)        

        find_package(Essential REQUIRED)

```

2. For your executable, add the library in 

```

        target_link_libraries(XXX Essential opengv gncso)

```