Object Tracklets

Object tracklets represent sequences of observations of the same object over time, forming the foundation for numerous computer vision tasks like multi-object tracking (MOT) and video instance segmentation. Current research focuses on improving tracklet generation and association by incorporating motion information, handling occlusions and uncertainties, and leveraging long-range temporal dependencies through techniques like transformers and recurrent neural networks. These advancements are crucial for applications such as autonomous driving, sports analytics, and video surveillance, enabling more robust and accurate object tracking in complex, dynamic environments.