Techniques for robust real-time multiple-object tracking with detection propagation and per-class optimization

Abstract

A data processing system implements obtaining a frame of video content at an object detection pipeline, the video content comprising a plurality of frames; analyzing the frame using an object detection model to detect a plurality of objects and associate each object with a confidence score; performing a primary matching operation on high confidence detection objects to associate the high confidence detection objects with an object track of a plurality of object tracks, the high confidence detection objects being objects associated with a confidence score that satisfies a confidence threshold; performing a secondary matching operation on low confidence detection objects to associate the low confidence detection objects with an object track of the plurality of object tracks, low confidence detection objects being objects associated with a confidence score that does not satisfy the confidence threshold; and outputting the plurality of object tracks.