Exercise_Recognition_MediaPipe

Real-Time Exercise Monitoring System With Pose Detection Using MediaPipe

Introduction

This project focuses on developing a real-time monitoring system for sports exercises using pose detection.

Project Overview

The system is designed to detect and analyze sports exercises, providing real-time feedback.

Objectives and Goals

• Develop a robust pose detection algorithm.

• Implement real-time monitoring and feedback.

• Ensure high accuracy and efficiency.

• Importance of the Project

This system aims to improve the quality of sports training by providing accurate real-time feedback, helping athletes and trainers optimize performance.

Methods Used

• Pose detection using MediaPipe Pose.
• Exercise Recognition using Machine Learning (Random Forest).

DataSet

• https://www.kaggle.com/datasets/muhannadtuameh/exercise-recognition?resource=download

• Exercise Detection Capabilities

This project is capable of detecting and monitoring the following exercises (both up and down movements):

• Squat
• Pull-up
• Sit-up
• Push-up
• Jumping Jacks

Conclusion

This project successfully demonstrates the feasibility and effectiveness of a real-time sports exercise monitoring system.

Demo

Output.Video.mp4