Progress
This week, I experimented with more methods to do the point. I wanted to get another webcam, but surge pricing due to the pandemic has caused webcams to go from $17 to $100. So, I am exploring solutions of using my phone or laptop webcam.
With pointing to 8 squares in a room, I was able to achieve 98% test accuracy and 98% validation accuracy with a SVM OVR model trained on 2700 poses. However, there were still error running it on a test video. I believe this is because I calculated the validation metrics from a held out percent of frames from the original video for training. So, I collected separate videos for train and validation. Also, I wanted to collect new data for the point to include pointing with both left and right hands.
The SVMs currently do not relay the fact that bins closer together are more similar, so I hope to try other model architectures like one neural net to predict the x and y coordinate of the bin separately. I could not have done this with the old dataset because there was not enough data.
I also built a visualization for the point to show in the demo.
Deliverables next week
I will train some new models with the dataset that I collected, and hope to get better results for the point on the test videos.
Schedule
On schedule.