Video & Image Processing - Assignment 2 Demo created as part of group research for Image & Video Processing paper This demo is wirtten in python using Mediapipe library and OpenCV.
Abstract This research study explores the application of MediaPipe technology and computer vision techniques in knee rehabilitation exercises. A Python software program is developed to integrate MediaPipe and analyze videos obtained from AccessPhysiotherapy, as well as self-recorded videos, to assess the effectiveness of MediaPipe in identifying and correcting knee exercises. The Angle Calculation Equation (ACE) is employed to accurately calculate angles between key points of the knee joint, enabling quantification and comparison of exercise performance. The findings demonstrate a successful replication of correct movements and a high degree of similarity in angle measurements between self-performed exercises and prerecorded videos, providing validation for the accuracy and potential of MediaPipe technology in enhancing accessibility and improving accuracy in knee rehabilitation exercises. While acknowledging the limitations associated with self-measurements, this study highlights the potential of MediaPipe in optimizing knee rehabilitation outcomes and suggests the need for future research to address these limitations and explore wider applications of MediaPipe technology in diverse knee rehabilitation settings
Keywords: Knee rehabilitation, MediaPipe, Computer vision, Motor rehabilitation, Angle Calculation Equation, Self-measurements.
Creative Commons https://www.youtube.com/watch?v=pTBnB6JLhF0