A Review of the Evolution of Vision-Based Motion Analysis and the Integration of Advanced Computer Vision Methods...

Area of Science:

• Biomechanics
• Human Movement Analysis
• Rehabilitation Technology

Background:

• Significant advancements in sports biomechanics and rehabilitation over recent decades.
• Challenges persist in developing motion analysis systems for accurate, timely, and unobtrusive kinematic data collection.
• Existing systems often require markers, controlled environments, and extensive processing, limiting routine application.

Purpose of the Study:

• To review the evolution of kinematic data extraction methods.
• To explore the potential of markerless motion capture systems in biomechanics.
• To introduce state-of-the-art computer vision research applicable to markerless motion capture.

Main Methods:

• Narrative review of methods for extracting kinematic information from images.
• Analysis of technological progression from manual to optoelectronic marker-based systems.
• Examination of emerging markerless systems driven by computer vision and machine learning.

Main Results:

• Current widely used systems in biomechanics and rehabilitation necessitate markers and controlled conditions.
• Markerless motion capture technology, influenced by the entertainment industry, is emerging.
• The accuracy and practicality of these new markerless systems require further investigation for biomechanical applications.

Conclusions:

• Markerless motion capture systems show promise for future biomechanics applications.
• Key challenges in accuracy and robustness for markerless systems must be addressed.
• State-of-the-art computer vision research is crucial for advancing markerless motion capture in biomechanics.