Rotation Search

Rotation search focuses on finding the optimal 3D rotation that best aligns sets of corresponding points or features, a crucial problem in various fields. Current research emphasizes developing robust and efficient algorithms, including iterative graph optimizers like RAGO for multiple rotation averaging and branch-and-bound methods like ROSIA for star identification, often incorporating techniques to mitigate noise and outliers. These advancements improve accuracy and speed, impacting applications such as computer vision (image translation, 3D reconstruction), robotics (camera pose estimation), and astronomy (star tracking). Furthermore, theoretical work investigates the conditions under which relaxation methods provide tight solutions to the underlying non-convex optimization problem.