File size: 2,517 Bytes
c9e1b42 f0f5e46 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 |
# GIST Multi-Camera Dataset
Collect and Annotate 3D Multi-Camera Multi-Object Tracking Dataset
# Prepare and print a checkerboard
1) Go to https://calib.io/
2) Pattern Generator (1) Target Type: Checkerboard,
3) Board Width [mm]: 841, (3) Board Height [mm]: 1189,
4) Rows: 6, (5) Columns: 4, Checker Width [mm]: 195
5) Download PDF
6) Print it two piceces of the PDF with A0 paper (841x1189 mm)
7) Glue them together precisely and tightly
# Install Packages
sudo apt install ffmpeg
pip install numpy==1.23.5 pandas==1.5.1 opencv-python==4.10.0.84
# Process
0. Videos are captured from Android devices using [RecSync](https://github.com/MobileRoboticsSkoltech/RecSync-android.git) with some modifications.
- Adding TrueTime dependency `'com.github.instacart:truetime-android:3.4'` to `app/build.gradle`. In `MainActivity.java` make sure to init TrueTime, `trueTimeInitialized.await();`
- `CameraController.java`, `long synchronizedTimestampNs = TrueTime.now().getTime();`. This change adapts one captured frame cooresponding to a timestamp obtained from TrueTime.
- `SoftwareSyncController.java`, `leaderAddress = InetAddress.getByName("172.17.3.136");` change IP address of leader server.
- If all Android devices are not the same model, we need to move some statements out of `if (isLeader) {})`
```
exposureSeekBar.setVisibility(View.VISIBLE);
sensitivitySeekBar.setVisibility(View.VISIBLE);
exposureSeekBar.setOnSeekBarChangeListener(
```
This setting allows us to ajust `sensitivity` and `exposure` of Android camera.
1. Videos are extracted using FFMPEG
2. Frames of each video are matched using timestamp obtained from `TrueTime`
3. `calibration_syncvideos.py` outputs calibration matrix from synchronized and extracted frames. Synchronized frames are saved in a folder name as `./GMC0715/S20`.
# Contact
Linh Ma (linh.mavan@gm.gist.ac.kr), Machine Learning & Vision Laboratory, GIST, South Korea
### Citation
If you find this project useful in your research, please consider citing by:
```
@article{linh2024inffus,
title={Track Initialization and Re-Identification for {3D} Multi-View Multi-Object Tracking},
author={Linh Van Ma, Tran Thien Dat Nguyen, Ba-Ngu Vo, Hyunsung Jang, Moongu Jeon},
journal={Information Fusion},
volume = {111},
year={2024},
publisher={Elsevier}
}
```
---
license: mit
---
|