Parametric Hand Model

Parametric hand models are 3D representations of hands, aiming to accurately capture their complex geometry and movement for applications like virtual reality and medical analysis. Current research focuses on improving realism and accuracy through incorporating biomechanical constraints (e.g., muscle and tendon dynamics), utilizing implicit representations and advanced neural networks (like transformers and graph convolutional networks) for efficient and high-fidelity reconstruction from various input modalities (RGB images, depth maps, point clouds). These advancements enable more realistic hand animation, improved pose estimation, and more accurate hand-object interaction modeling, impacting fields such as computer graphics, robotics, and healthcare.