I spent the last week drafting, refining, and presenting our final design presentation, as well as preparing to give said presentation before the class.
Further, I did some more research into gesture recognition and found that many more studies used a pose estimation algorithm to identify hand landmarks and run the estimated pose through their model for gesture detection. This was in contrast to my initial approach, which was to feed in camera data directly. Presented with this new paradigm and upon further consideration this makes sense, as this method eliminates much of the noise of background colors and images and reduces the number of features the model will need to learn.
This week the adaptation of the pre-trained model will begin, as well as work on the final design documents/report. We are still waiting on AWS access to GPUs, which will aid in the speedy training of our model.