Vop2el

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Vop2el is a simple, fast and accurate stereo visual odometry algorithm

Vop2el 최신버젼 다운로드

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# Vop2el

The goal of this repository is to provide a stereo visual odometry algorithm based on the  methods described in [SOFT2](https://lamor.fer.hr/images/50036607/2022-cvisic-soft2-tro.pdf) paper.

Note: This algorithm relies on a known camera calibration matrix and a known extrinsic transformation between the left and right cameras of the stereo camera.

![alt text](https://raw.githubusercontent.com/Vop2elToolkit/Vop2el/main/doc/result_sequence_00_kitti.gif)

## Dependencies

This project has been tested and verified to build successfully on Ubuntu 20.04 LTS with the following dependencies.

- Eigen 3.4

- Ceres 2.2

- OpenMP

- For OpenCV, we use a slightly modified version that will be built during the build of this project.

## Build and install

To build and install this project on linux, follow the steps below:

```bash
git clone https://github.com/Vop2elToolkit/Vop2el.git

cd Vop2el && git submodule update --init --recursive

mkdir ../Vop2el-build && cd ../Vop2el-build
```

#### Notes:
- ```vop2el``` has two build modes: with and without Rerun SDK 
- When building without Rerun SDK, users will receive a ```csv``` file containing the estimated poses after processing a sequence of images.
- When building with Rerun SDK, users will get a real time visualization of estimated poses, and receive a ```csv``` file containing the final poses after processing a sequence of images

### Build without Rerun SDK

```bash
cmake ../Vop2el -DBUILD_WITH_RERUN=OFF

cmake --build .
```

### Build with Rerun SDK for visualization

Download the Rerun viewer (version 0.17.0) from https://github.com/rerun-io/rerun/releases

```bash
cmake ../Vop2el

cmake --build .
```

## Run

To run this project on linux, follow the steps below (Skip the initial two steps when building without Rerun):

- Launch the Rerun viewer

- In the Rerun viewer, open the blueprint file ```vop2el/vop2el_src/test/vop2el.rbl```

- Run Vop2el

```bash
./bin/Vop2elTester /path/to/left/images/folder \
                   /path/to/right/images/folder \
                   /path/to/config/ini/file \
                   /path/to/estimated/poses/text/file \
                   /path/to/ground/truth/poses/text/file(optional)
```

![alt text](https://raw.githubusercontent.com/Vop2elToolkit/Vop2el/main/doc/rerun_sequence_00_kitti.gif)

### Notes:
- Users should rely on parameters ini file provided in test folder.
- Set use_ground_plane_correction to false in the parameters file if the robot is non-terrestrial or if the distance and normal to the ground plane are unknown.
- To improve processing time, the simplest way is to reduce value of max_number_matches in parameters file.
- In the estimated poses text file, each pose will be written as a single line representing a row-major 3x4 matrix.
- The last argument mentioned in the command above is optional. When provided, it is used solely to compute translation and rotation error metrics between the estimated and ground truth poses.

## Differences with SOFT2
| SOFT2 | Ours |
| ---                              | ---        |
| Automatic computing of ground plane normal vector and distance to ground plane | The user needs to provide the ground plane normal vector and distance to ground plane if he would like to use patch correction feature |
| Use SOFT algorithm to estimate initial relative pose | Use Lucas–Kanade optical flow to estimate initial matches, followed by a RANSAC to estimate initial relative pose |
| Bundle adjustment | No bundle adjustment
| Extrinsic camera rotation is optimized during scale computing | For now, the extrinsic camera rotation is deemed satisfactory and will not undergo optimization during the algorithm

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