- The most significant risk that could happen to our project is not meeting one of our main requirements of at least 5 frames per second. We are working on improving our current rate of 4 frames per second by having some openCV algorithms run GPU, in particular the dnn module which detects where a face in the image is. If this optimization does not noticeably increase our performance then we plan on using our back-up plan of moving some of the computation to AWS so that the board is faster.
- This week we have not made any major changes to our designs or block diagrams.
- In terms of our goals and milestones, we are a little ahead of our original plan. Because of this, we are deciding which stretch goals we should start working on and which of our stretch goals are feasible within the remaining time we have. We are currently deciding between pose detection or phone detection.
Carnegie Mellon ECE Capstone, Spring 2021: Adriana Martinez, Jananni Rathnagiri, Evann Wu