Marker Less Mocap

Marker-less motion capture (MoCap) aims to reconstruct 3D human movement without relying on retroreflective markers, offering greater freedom of movement and reduced cost compared to traditional methods. Current research focuses on improving accuracy and robustness using diverse data sources, including RGB cameras, depth sensors, inertial measurement units (IMUs), and even smartwatches, often integrating these modalities through deep learning models like transformers and recurrent neural networks, or optimization techniques that leverage visual and inertial cues. These advancements are significant for various fields, enabling more accessible and versatile motion capture for applications ranging from animation and robotics to clinical analysis and virtual reality.