Yoga posture recognition using the deep learning process

Abstract

Yoga is one of the best activities from home to preserve our physical condition in the present epidemic. Yoga, on the other hand, is all about performing the 82 Yoga Asanas correctly over the course of six classes. Regrettably, not everyone have the knowledge or can perform yoga accurately. So to do yoga poses correctly we will have to find a yoga instructor, but it can be very hard and expensive to find yoga instructors considering all possible general situation and status. Using Deep Learning(DL), picture categorization and various machine learning approaches, we attempted to build a system or a model that will operate as a self-instructor of Yoga for the user to classify different poses of yoga to distinguish accurate pose in our thesis. It will assist the user in performing Yoga correctly by recognizing errors in their Yoga Asanas. In a nutshell, this section will cover several posture estimation, key point detection, and pose categorization techniques. Moreover, we tried ensemble modeling as a booster to improve the pose prediction accuracy as much as possible.

Description

Cataloged from PDF version of thesis.
Includes bibliographical references (pages 36-37).
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.

Keywords

Yoga posture, Deep learning, Learning theory, Artificial intelligence (AI)

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