AI TRAINER (Human Pose Estimation and Correction Using Machine Learning )

Abstract

Human pose estimation is a rapidly advancing field in computer vision, with applications spanning sports, healthcare, fitness, and human-computer interaction. The primary goal is to accurately detect and interpret human body key-points, which can be used to assess and correct postures and movements. Recent advancements in deep learning have enabled significant progress in pose estimation accuracy. This paper proposes a novel approach to enhance human pose estimation and correction using a deep learning-based AI trainer system. The AI trainer leverages machine learning algorithms to detect human poses in real-time and utilizes a feedback system to provide corrective insights.