RGBD Tracker

RGBD tracking focuses on accurately locating objects in video sequences using both color (RGB) and depth (D) information, aiming for robust performance even in challenging scenarios. Current research emphasizes developing unified models capable of handling various data modalities (RGB, depth, thermal, event data) efficiently, often employing transformer-based architectures and techniques like low-rank factorization for cross-modal fusion. These advancements improve tracking accuracy and robustness, impacting applications such as robotics, augmented reality, and autonomous driving by enabling more reliable object perception.