Resources

Here we give credit to the libraries and software we used to develop this tool.

OpenCV

We used OpenCV for image and video loading. We also used it for blob analysis when solving the markered video problem.

OpenPose

We employ OpenPose for our solution of the markerless video problem. OpenPose provides us with keypoint estimation of the feet, which we then can send into our post-detection analysis.

PyTorch

We used PyTorch when developing and testing the Deep Convolutional Tracker.

Python Libraries

We used numpy for signal analysis, matplotlib for plotting, PyQT for the welcoming GUI

PyCharm

We primarily used PyCharm as our IDE.