Yoga Posture Recognition Through Computer Vision and Deep Learning

Abstract

Abstract: India is the place where yoga's science and discipline originated 5,000 years ago. The development of it in ancient India occurred through the Indus-Sarasvati civilization. The Indian subcontinent is where this ancient practice originates,and it has been cherished for its multifaceted benefits that encompass physical, mental, and spiritual. Through asana, meditation, and other breathing techniques, harmony is brought to both body and mind. It also brings peace to the mind. The rise in stress in today's modern lifestyle has led to a global growth in the popularity of yoga. The goal of yoga is to mechanically align the body with effort on the muscles, ligaments, and joints to achieve optimal posture. If the asanas are not performed properly, strain in the joints, ligaments, and backbone can occur, which can have an impact on the hip joints. Therefore, it is vital to maintain correct yoga postures while performing various asanas. The availability of yoga posture prediction and automatic movement analysis is now possible due to the development of computer vision algorithms and sensors. In this work, a framework for recognizing a yoga posture from an image has been built using deep learning techniques such as convolutional neural networks (CNN) and machine learning (ML). The CNN layer is used to extract characteristics from the keypoints, and it is succeeded by a large short-term recollection that recognizes the sequence in which a set of frames occurs in order to make predictions. The stances are then categorized as either correct or inappropriate. The system will provide the user with feedback and display the correctness of posture if the right attitude is detected. This review paper synthesizes the current state-of-the-art in the field of yogic intelligence, focusing on the application of computer vision and deep learning techniques for recognizing yoga postures