In International journal of yoga
In recent days, Yoga is gaining more prominence and people all over the world have started to practice it. Performing Yoga with proper postures is beneficial. Hence, an instructor is required to monitor the correctness of Yoga postures. However, at times, it is difficult to have an instructor. This study aims to provide a system that will act as a personal Yoga instructor and practitioners can practice Yoga in their comfort zone. The device is interactive and provides audio guidance to perform different Yoga asanas. It makes the use of a camera to capture the picture of the person performing Yoga in a particular position. This captured pose is compared with the benchmark postures. A pretrained deep learning model is used for the classification of different Yoga postures using a standard dataset. Based on the comparison, the practitioner's posture will be corrected using a voice message to move the body parts in a certain direction. As the device performs all the operations in real-time, it has a quick response time of a few seconds. Currently, this work aids the practitioners in performing five Asanas, namely, Ardha Chandrasana/Half-moon pose, Tadasana/Mountain pose, Trikonasana/Triangular pose, Veerabhadrasana/Warrior pose, and Vrikshasana/Tree pose.
Kishore D Mohan, Bindu S, Manjunath Nandi Krishnamurthy
2022
Human posture recognition, Mediapipe, Yoga, pose detection and pose correction, real-time
