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Consistent multi-layer subtask tracker via hyper-graph regularization
2017
Pattern Recognition
Most multi-task learning based trackers adopt similar task definition by assuming that all tasks share a common feature set, which can't cover the real situation well. In this paper, we define the subtasks from the novel perspective, and develop a structured and consistent multi-layer multi-subtask tracker with graph regularization. The tracking task is completed by the collaboration of multi-layer subtasks. Different subtasks correspond to the tracking of different parts in the target area.
doi:10.1016/j.patcog.2017.02.008
fatcat:hj7iif3iefcknirwm4j63vbyly