Orientation Representation

Orientation representation focuses on effectively encoding and manipulating rotational data, crucial for various applications from robotics to medical image analysis. Current research emphasizes robust and efficient representations, particularly leveraging Lie group theory and implicit neural representations (INRs) to address challenges like computational cost and mathematical correctness in learning frameworks. These advancements improve accuracy and efficiency in tasks such as object detection, shape matching, and motion planning, impacting fields ranging from autonomous systems to medical imaging. The development of orientation-aware algorithms is driving progress in several scientific domains and enabling more sophisticated applications.