Rotation Estimation

Rotation estimation, the process of determining the orientation of an object or camera in 3D space, is a crucial task in computer vision and robotics, aiming for accurate and robust solutions even under challenging conditions like noise, limited viewpoints, or dynamic scenes. Current research emphasizes developing efficient algorithms and model architectures, such as those based on Gaussian belief propagation, spherical harmonics, and deep neural networks, to address these challenges, often incorporating techniques like uncertainty quantification and outlier rejection. These advancements are driving improvements in applications ranging from visual odometry and SLAM to 3D object pose estimation and autonomous navigation, impacting fields like robotics, augmented reality, and medical imaging.