The detection and rectification for identity-switch based on unfalsified control
원문 초록
The purpose of multi-object tracking (MOT) is to continuously track and identify objects detected in videos. Currently, most methods for multi-object tracking model the motion information and combine it with appearance information to determine and track objects. In this paper, unfalsified control is employed to address the ID-switch problem in multi-object tracking. We establish sequences of appearance information variations for the trajectories during the tracking process and design a detection and rectification module specifically for ID-switch detection and recovery. We also propose a simple and effective strategy to address the issue of ambiguous matching of appearance information during the data association process. Experimental results on publicly available MOT datasets demonstrate that the tracker exhibits excellent effectiveness and robustness in handling tracking errors caused by occlusions and rapid movements.
함께 살펴볼 논문
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ReaMOT: A Benchmark and Framework for Reasoning-based Multi-Object Tracking
Asynchronous Multi-Object Tracking with an Event Camera
FusionTrack: End-to-End Multi-Object Tracking in Arbitrary Multi-View Environment
LiDAR MOT-DETR: A LiDAR-based Two-Stage Transformer for 3D Multiple Object Tracking
Towards Accurate State Estimation: Kalman Filter Incorporating Motion Dynamics for 3D Multi-Object Tracking
The Mean of Multi-Object Trajectories
토론
이 논문과 연결된 포럼 글이 아직 없습니다.