AI-Based Yoga Pose Estimation for Android Application


Authors : Girija Gireesh Chiddarwar; Abhishek Ranjane; Mugdha Chindhe; Rachana Deodhar; Palash Gangamwar

Volume/Issue : Volume 5 - 2020, Issue 9 - September

Google Scholar : http://bitly.ws/9nMw

Scribd : https://bit.ly/36u0wQO

DOI : 10.38124/IJISRT20SEP704

The importance of yoga is renowned worldwide and its health benefits, which were preached by ancient sages, have stood the test of time. Even though yoga is becoming preeminent, there are important challenges faced while doing yoga such as performing it with incorrect form, the classes being expensive and the shortage of time in our busy lives. Computer vision techniques exhibit promising solutions for human pose estimation. However, these techniques are seldom applied in the domain of health or exercise, with no literature or projects cited specifically for yoga. This paper surveys the various technologies that can be used for pose estimation and concludes the best method based on the usability for an android application. The paper then discusses the methodology that will be used to deploy the yoga pose estimation on an android application, how the app is modeled and the working of each component is explained.

Keywords : AI; Yoga; Deep Learning; PoseNet; Android.

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