Human Pose Estimation using Artificial Intelligence with Virtual Gym Tracker

Artificial intelligence has become essential in a wide range of industries, including the fitness industry. Human pose estimation is becoming increasingly popular. Human pose assessment can be established based on Artificial Intelligence or Machine Learning techniques, where sample data is employed in system with the help of trained models, after that place the joints of human body by video or picture. After that joints of that person’s body have been confined and further utilize in a variety of purposes, such as determining a person’s gait cycle or their subsequent motions of a specialized athlete in order to study about the physical methods and approaches for acquiring his or her achievement. One major application of Human pose valuation could be in the area of gym trainer tracker which helps in struggling gymnasts in order to accomplish their goals. Machine learning technology can aid in counting repetitions of any exercise during weightlifting or CrossFit events. Pose estimation is used to identify key points, and the angle between key points (elbow and shoulder) is measured. In this research paper, we can estimate the up and down stages in the Gym tracker based on the angle’s threshold following that, the tracker predicts all 33 position key points.