Euler Angle
Euler angles represent a fundamental method for describing three-dimensional rotations, crucial in fields ranging from robotics to computer vision. Current research focuses on improving the accuracy and robustness of Euler angle estimation, particularly addressing ambiguities inherent in their representation and developing methods for efficient computation, often leveraging machine learning techniques like support vector machines and neural networks within frameworks such as NeRFs (Neural Radiance Fields). These advancements are vital for applications requiring precise pose estimation, such as head pose tracking in augmented reality or accurate system identification in physics-based simulations, improving the reliability and performance of these systems.