Deep SORT

Previously, we looked at one of the simplest trackers. In this section, we will use richer features from CNNs to perform tracking. Deep SORT[2] is a recent algorithm for tracking that extends Simple Online and Real-time Tracking[3] and has shown remarkable results in the Multiple Object Tracking (MOT) problem.

In the problem setting of MOT, each frame has more than one object to track. A generic method to solve this has two steps:

  • Detection: First, all the objects are detected in the frame. There can be single or multiple detections.
  • Association: Once we have detections for the frame, a matching is performed for similar detections with respect to the previous frame. The matched frames are followed through the sequence to get the ...

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