Score refinement for confidence-based 3D multi-object tracking

Understand

Multi-object tracking is a critical component in autonomous navigation, as it provides valuable information for decision-making.

• Many researchers tackled the 3D multi-object tracking task by filtering out the frame-by-frame 3D detections; however, their focus was mainly on finding useful features or proper matching metrics.
• Our work focuses on a neglected part of the tracking system: score refinement and tracklet termination.
• We show that manipulating the scores depending on time consistency while terminating the tracklets depending on the tracklet score improves tracking results.