This week was a cool week. I learned a lot from the ethics lesson on Wednesday. After the discussion with the other teams, I learned that the biggest concern for most engineering projects is data collection and data usage, which is something that may be lacking in our project explanation. I will keep this in mind for our final presentation.
I spent a lot of time improving the gesture recognition algorithm. With one single data collection, we are most likely not able to identify what gesture is being done. I improved it by looking at the frequency of the gestures guessed over n data collections. The accuracy improved for every gesture except zoom out, which makes sense because the beginning of the gesture looks like a swipe.
We collected more data so that we can see if the algorithm fits different variations of the the gesture. We noticed that there is high variability in the accuracy of our algorithm based on the speed and location in which we move our fingers. I decided to look into varying the n data collections and the polynomial that the data is currently being fitted into to accommodate our two discoveries. I am working with the data in Excel and am planning on looking at statistics to determine which combination yields the highest result.
Screenshot of pinching in data with n data against the order of the polynomial
I think that although this is a slow week, I’m going to be working hard to improve the algorithm before the interim demo day. Although our project is in the process of being integrated, this is a critical part of achieving our design metrics. I’m planning on meeting with my team outside of class on Monday and Tuesday so that we can work together to improve the algorithms.
Apart from algorithm updates, I need to talk to a professor about the Jetson. I’ve started playing with the Raspberry Pi, which is easier to work with since I have prior experience. I will spend Wednesday working on this part. Next week will surely be busy, but these deliverables are critical to the success of the interim demo.