Absolute Pose
Absolute pose estimation aims to determine the precise location and orientation of a camera (or other sensor) within a 3D environment using image data and/or other sensor inputs. Current research focuses on improving the accuracy and efficiency of pose estimation, particularly in challenging scenarios like those with limited features, significant viewpoint changes, or noisy data, employing techniques such as geometric algorithms, deep learning models (including transformers and convolutional neural networks), and fusion of multiple sensor modalities (e.g., visual-inertial). These advancements have significant implications for applications like augmented reality, robotics, autonomous navigation, and 3D scene reconstruction, enabling more robust and reliable operation in complex environments.