Rigid Motion Tracking

Rigid motion tracking aims to accurately determine the three-dimensional movement of objects, a crucial task in diverse fields like medical imaging and robotics. Current research emphasizes robust algorithms, often incorporating convolutional neural networks (CNNs), particularly those leveraging SE(3) equivariance for improved rotation handling, and integrating physics-based models for more realistic simulations. These advancements are driving improvements in applications such as medical image registration, surgical guidance, and autonomous systems navigation, where precise tracking of objects is essential for accurate analysis and control.