HUMAN POSE ESTIMATION

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 keypoints, 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 . the reference papers related to this technology specifes differenrt approaches towards solutions Ali Raza(2023)uses skeleton landmark method for physiotherapy exercise correction, Atima Tharatipyakul(2024)focus deep learning approach to estimate & providing feedback, Sakshi Somani(2021)paper specify the number of exercise providing pre buit dataset , Naveen Kumar(2023)focuses on accuracy and delivering low cost solutions to user Neetu Faujdar(2023) model predict overall 33 position key point and also estimate angle threshold