Abstract
Yoga’s popularity is increasing daily. Doing Yoga regularly helps physically, mentally, and spiritually. Many people practice yoga without any formal training. However, practicing yoga incorrectly or even without proper supervision can lead to serious health problems such as stroke, nerve damage, and so on. As a result, there is a need for scientific posture analysis ensuring appropriate yoga posture is an essential aspect to consider. Pose identification strategies are effective in identifying posture and assisting people in performing yoga more effectively. Due to the paucity of data and real-time positioning, position detection is a difficult task. In this paper, we have done an extensive literature survey and offer a method for real-time pose estimation that uses the deep neural network(DNN) model to detect and fix errors in a person’s stance.
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