Pose Tracking

Pose tracking, the process of estimating and following the position and orientation of an object or person over time, is a crucial area of research with applications ranging from robotics and augmented reality to human-computer interaction and autonomous driving. Current research focuses on improving accuracy and robustness, particularly in challenging conditions like occlusions, dynamic environments, and limited sensor data, employing techniques like deep learning, model predictive control, and Kalman filtering within various frameworks such as visual-inertial odometry and multi-view geometry. These advancements are driving progress in areas such as robot manipulation, human activity understanding, and improved navigation systems for vehicles and mobile robots.