Intelligent Assessment Through Human Motion Recognition

Human motion recognition (HMR) has emerged as a pivotal technology across various domains, enabling intelligent assessment of performance and behavior. This survey examines advancements in HMR methodologies, including computer vision techniques, deep learning, and machine learning algorithms, highlighting how they facilitate real-time analysis and enhance decision-making processes. Additionally, address the challenges inherent in data quality, privacy concerns, and algorithmic limitations that impact the effectiveness of HMR systems. This research introduces an innovative approach employing computer vision techniques to evaluate performance and deliver instant feedback on body positioning during exercise routines. This method enables immediate self-adjustment and encouragement, even in the absence of professional supervision. Our system utilizes a versatile learning framework to analyze live expert demonstrations or recorded video content, promoting correct form and enhancing exercise outcomes