vmarquet / Table Tennis Computer Vision
Apply computer vision to table tennis for match / training analysis
Stars: ✭ 48
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Description
The goal of the project is to apply computer vision with OpenCV, and maybe depth sensors like Kinect, to keep track of the score at table tennis. Furthermore, data analysis can be made to infer statistics about the players.
Installation
OpenCV 2.4
Mac OS X
brew tap homebrew/science && brew install opencv
The OpenCV is usually installed in /usr/local/Cellar/opencv/.
To use the Python bindings, you must create symlinks in the directory where Python is installed, usually in /Library/Python/2.7/site-packages/, pointing to the OpenCV directory.
sudo ln -s /usr/local/Cellar/opencv/2.4.11/lib/python2.7/site-packages/cv.py /Library/Python/2.7/site-packages/cv.py
sudo ln -s /usr/local/Cellar/opencv/2.4.11/lib/python2.7/site-packages/cv2.so /Library/Python/2.7/site-packages/cv2.so
Advancement
- First step: camera calibration
- Second step: distortion correction
- Third step: table lines detection
- Fourth step: ball tracking
- Fifth step: 3D position calculation with stereovision
Distortion correction
| Before | After |
|---|---|
 |
 |
Table lines detection
| Hough transform | Rectangle detection | Hough after k-mean |
|---|---|---|
 |
 |
 |
Ball tracking
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