External Tracker
External trackers aim to accurately estimate the position and orientation (6 DoF) of objects or individuals over time, finding applications in diverse fields like robotics, virtual reality, and video surveillance. Current research emphasizes improving tracking robustness and accuracy in challenging conditions (e.g., low light, occlusion, crowded scenes) using various approaches, including transformer networks, graph neural networks, and Siamese networks, often incorporating appearance and motion features for improved data association. These advancements are driving progress in areas such as autonomous driving, human-computer interaction, and medical imaging, where precise and reliable object tracking is crucial.
Papers
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