This week I integrated my facial detection classifier into the MVP. In addition, I made some changes to improve the accuracy of the classifier. I am still getting a relatively high rate of false-positives, and I have been trying to reduce this by continuing to conduct hard-negative mining and improving the training set. While I have been waiting for the classifier to train on AWS (which takes a couple days), I have also started looking into the raised-hand detection code and how I could improve it. I have started experimenting with some ideas that I found in various research papers.
Over the next week, I plan on retraining my classifier on AWS with my new training set and finish writing the cascading classifiers code. I will also continue working on the raised-hand detection code.
Overall, I think I am on schedule. I have an implementation of facial detection that works and has been integrated into the MVP. I have also began working on the raised-hand detection code. Over the next few weeks the goal will be to work on optimizing results and improving accuracy.