Pose Estimation

The goal of this project was to identify the pose of gym-goers in real time using a Raspberry Pi 4, camera module, and AI. A program I wrote uses this pose information and checks if people are doing a series of exercises such as squats, curls, bench presses, etc. correctly and with a consistent speed. If they do the exercises incorrectly or too slowly, then the robot initiates a speaker with a pre-recorded set of "words of encouragement". The pose estimation is achieved using an open source library by Google called Mediapipe while the logic that identifies exercises and the tricks that I used to make this run in real time were my own. For instance, the model complexity of pose detection models can be adjusted and the confidence threshold for detections can be tuned. Additionally, I multi-threaded the program to have one thread contain the detections while the other thread contain the logic to identify exercises and initiate the hardware speakers to encourage the person doing the exercise. This greatly improved real-time performance.