https://github.com/zju-fast-lab/fast-dynamic-vision
Detecting and Tracking Dynamic Objects with Event and Depth Sensing
https://github.com/zju-fast-lab/fast-dynamic-vision
Last synced: over 1 year ago
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Detecting and Tracking Dynamic Objects with Event and Depth Sensing
- Host: GitHub
- URL: https://github.com/zju-fast-lab/fast-dynamic-vision
- Owner: ZJU-FAST-Lab
- License: gpl-3.0
- Created: 2021-03-05T11:57:11.000Z (over 5 years ago)
- Default Branch: main
- Last Pushed: 2021-11-13T10:56:27.000Z (over 4 years ago)
- Last Synced: 2025-04-04T11:37:24.493Z (over 1 year ago)
- Language: C++
- Homepage:
- Size: 30.1 MB
- Stars: 135
- Watchers: 10
- Forks: 33
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# FAST-Dynamic-Vision
**FAST-Dynamic-Vision** is a system for detection and tracking dynamic objects with event and depth sensing.
## 0. Overview
**FAST-Dynamic-Vision** is a detection and trajectory estimation algorithm based on event and depth camera.
**Related Paper**: [FAST-Dynamic-Vision: Detection and Tracking Dynamic Objects with Event and Depth Sensing](https://arxiv.org/abs/2103.05903), Botao He, Haojia Li, Siyuan Wu, Dong Wang, Zhiwei Zhang, Qianli Dong, Chao Xu, Fei Gao
**Video Links**: [YouTube](https://www.youtube.com/watch?v=QPpwppeE_x0&ab_channel=FeiGao), [Bilibili](https://www.bilibili.com/video/BV11U4y1p7EF/)
## 1. File Structure
- **event-detector**: Key modules with event processing, depth estimation, motion compensation and object detection.
- **bullet_traj**: modules for trajectory estimation in 3D world frame.
## 2. Setup
**Requirement**: Ubuntu 18.04 with ros-desktop-full installation; [**Ceres Solver**](http://ceres-solver.org/installation.html); OpenCV 3; [opencv_contrib](https://github.com/opencv/opencv_contrib)
> NOTION: If you are using Ubuntu 20.04 and failed to build this project with some linking error, please edit `CMakeLists.txt` and specify `OpenCV 4` .
**Step 1**: Installation
```
sudo apt install libeigen3-dev build-essential libopencv-contrib-dev
```
**Step 2**: Clone the thie repo
```
git clone https://github.com/ZJU-FAST-Lab/FAST-Dynamic-Vision.git --branch=main
```
**Step 3**: build this project
```
cd FAST-Dynamic-Vision
catkin_make
```
## 3. Run a simple demo
Please clone branch `dataset` to use our demo dataset. It was recorded via **DVXplorer**, which provides 640x480 resolution.
### 3.1 Event-based motion compensation and object detection
This demo shows the performance of object detection and tracking algorithms.
```
source devel/setup.bash
roslaunch detector detection.launch
```
### 3.2 Moving ball trajectory estimation under motion-cap system
This demo shows detect and estimate the 3D trajectory of a throwing ball utilizing event and depth camera. The ground truth of the ball trajectory is captured by Vicon Motion Capture system.
```
source devel/setup.bash
roslaunch bullet_traj_est demo_traj_est_rviz.launch
```
## 4. Licence
The source code is released under [GPLv3](http://www.gnu.org/licenses/) license.
## 5. Maintaince
For any technical issues, please contact Haojia Li([hlied@connect.ust.hk](mailto:hlied@connect.ust.hk)), Botao He([botao.he@njit.edu.cn](mailto:botao.he@njit.edu.cn)), Siyuan Wu ([siyuanwu99@gmail.com](mailto:siyuanwu99@gmail.com)), or Fei GAO ([fgaoaa@zju.edu.cn](mailto:fgaoaa@zju.edu.cn)).
For commercial inquiries, please contact Fei GAO ([fgaoaa@zju.edu.cn](mailto:fgaoaa@zju.edu.cn)).