Deformable Shape

Deformable shape analysis focuses on understanding and representing the dynamic changes in three-dimensional objects. Current research emphasizes developing robust methods for keypoint detection and tracking on deforming surfaces, often employing techniques like geodesic distance preservation and kernel methods for global registration. These advancements are crucial for applications ranging from 3D reconstruction and pose estimation in computer vision to robotics and the simulation of complex physical interactions, particularly for objects with little or no texture. The development of efficient and accurate models for deformable shapes is driving progress across multiple scientific disciplines.