I spent the first half of the week preparing for the Project Proposal presentation. Over the weekend, I worked on fleshing out the requirements, finding quantitative measures, creating diagrams, and putting together the slides. I collaborated with my teammates over Zoom calls to refine the presentation as well. Since we all agreed that I would be doing the presentation, I spent time practicing to ensure I could explain the project clearly rather than just reading from the slides. I rehearsed both by myself and in front of others in order to gain feedback and complete the presentation as thoroughly as I could. I ended up presenting on Wednesday, so I continued to spend Monday and Tuesday practicing the presentation.
After the presentation was over, I began to shift my focus onto looking deeper into the computer vision aspect of our project. I spent time researching the Mediapipe and OpenCV libraries and reading/watching tutorials on how other people have utilized the libraries. I have done some computer vision work in the past (but nothing of this scale), so I brushed up on the OpenCV library in python. I played around with some simple test scripts that could be used for the first part of the CV algorithm that opens my computer camera and saves these images to my computer (image below). This could be the base of the project as it allows us to take camera images and use that for continued processing for the rest of the project.
In our schedule, we allotted this week to be more of an introductory week, where we will try to get familiar with the libraries and overall better understand what our project will entail. Additionally, because we recently pivoted our project, I hope to gain an even clearer understanding of what we need to do through our weekly meeting with our faculty advisor next week. In terms of the technical requirements, next week I will try to get more familiar with the Mediapipe framework and explore specifically how we will get key points of a user’s body when they are dancing.
