ByteTrack: A Simple Yet Effective Multi-Object Tracking Technique

A simple, effective, and a generic association method to track objects by associating almost every detection box instead of just the high score ones

The goal of Multi-Object Tracking(MOT) is to draw the bounding boxes around objects by detecting and identifying them in a video and then maintaining their trajectories with high accuracy.

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MOT takes a single continuous video as an input and splits it into discrete frames at a specific frame rate. The output of the MOT is

• Detection: what objects are present in each frame
• Localization: where objects are in each frame
• Association: whether objects in different frames belong to the same or different objects

Existing MOT Techniques

MOT methods based on tracking by detection utilize the most powerful detection techniques like one-stage object detector RetinaNet, CenterNet, or YOLO series to obtain high-performance tracking. Tracking by detection directly uses detection boxes on a single image for tracking…