Surface Matching

Surface matching aims to find correspondences between two 3D surfaces, a crucial task in various fields like medical image analysis and robotics. Current research focuses on improving the accuracy and efficiency of matching algorithms, employing techniques like biomechanical models (often finite element methods), hierarchical binary surface encoding, and neural network-based adjoint methods to handle complex deformations and partial matches. These advancements are driving progress in applications such as image-guided surgery, object pose estimation, and LiDAR-inertial odometry, where precise and computationally efficient surface registration is critical.