3D Registration

3D registration aims to align multiple 3D datasets, such as point clouds or meshes, by finding the optimal transformation (rotation and translation) that maps corresponding points in different coordinate systems. Current research emphasizes developing robust and scalable algorithms, focusing on techniques like iterative closest point (ICP) variants, expectation-maximization (EM) methods, and deep learning approaches including diffusion models and graph neural networks, to handle outliers, large transformations, and complex deformations. These advancements are crucial for various applications, including robotics, autonomous driving, medical image analysis, and 3D modeling, enabling accurate scene reconstruction, object tracking, and medical image fusion.