The article reviews the evolution of human movement capture methods, leading to the development of markerless motion capture for biomechanical applications. Traditional methods require markers or fixtures, which can introduce artifacts and limit natural movement analysis. Markerless techniques, using visual hulls and articulated ICP algorithms, offer a non-invasive, accurate alternative for capturing 3D human movement. These methods are crucial for clinical and research applications where natural movement patterns must be studied without artificial stimuli. The paper discusses the challenges of marker-based systems, such as skin movement artifacts and the need for precise joint tracking. It highlights the potential of markerless systems to provide accurate kinematic data, validated against marker-based systems. The study demonstrates the feasibility of markerless motion capture using visual hulls and detailed 3D models, showing that it can achieve high accuracy in measuring joint angles and movement patterns. The results indicate that markerless systems can provide meaningful assessments of human movement, particularly in clinical settings where subtle changes in gait are important. The paper emphasizes the importance of developing markerless techniques that are both accurate and practical for biomechanical and clinical applications.The article reviews the evolution of human movement capture methods, leading to the development of markerless motion capture for biomechanical applications. Traditional methods require markers or fixtures, which can introduce artifacts and limit natural movement analysis. Markerless techniques, using visual hulls and articulated ICP algorithms, offer a non-invasive, accurate alternative for capturing 3D human movement. These methods are crucial for clinical and research applications where natural movement patterns must be studied without artificial stimuli. The paper discusses the challenges of marker-based systems, such as skin movement artifacts and the need for precise joint tracking. It highlights the potential of markerless systems to provide accurate kinematic data, validated against marker-based systems. The study demonstrates the feasibility of markerless motion capture using visual hulls and detailed 3D models, showing that it can achieve high accuracy in measuring joint angles and movement patterns. The results indicate that markerless systems can provide meaningful assessments of human movement, particularly in clinical settings where subtle changes in gait are important. The paper emphasizes the importance of developing markerless techniques that are both accurate and practical for biomechanical and clinical applications.