The biggest threat to our project are issues with the swimming pool footage. We haven’t been able to find a pool that is willing to help us get perfectly aerial footage of a swim practice/competition, and there isn’t any footage available online that exactly meets our needs. Because of this, we have altered the scope of our project to require the client to manually outline the lanes in the pool that we should be analyzing, and will place additional constraints on the input video as the need arises.

One major change that we made to our project is abandoning OpenPose for stroke classification. We spent two entire class periods trying to get sample code working, but we couldn’t even get the library to compile. OpenPose is designed to be used on GPUs, and without these resources we decided it would be a more substantial project if we did our own limbic detection with OpenCV.

We are still on schedule to complete our project on time, but we have changed the order in which we are implementing things. Because we are still waiting to hear back about collecting better footage, we decided to push back motion detection in exchange for getting a web app up and running. Even though this wasn’t scheduled until the end of March, we have deployed a very basic outline of PoolTrackerDDR on an AWS instance.