Progress
This week, I worked on the final version of the point model. To get the best performance, I included noise into the pointing dataset, used less keypoints to focus on the arms, and added location as a feature for point classification.
The best performing model on the newest dataset had a validation accuracy of 96%.
I also built a point trigger to let users choose where to activate the point in the final application. This allows the point to operate smoothly with the gesture recognition system at ~27 FPS, whereas running the point model on every frame is 28FPS.
We also planned what we needed for our demo video.
Deliverables next week
Next week, we will give our final presentation and put together our video.
Schedule
On schedule.