Introduction Multi-object tracking (MOT) is a task in which an algorithm must detect and track multiple objects in a video. Most known algorithms are based on using simple detectors (e.g. YOLO) designed for processing individual images. The overall method involves separately using a detector on consecutive video frames and then matching the corresponding bounding boxes […]

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​Introduction Multi-object tracking (MOT) is a task in which an algorithm must detect and track multiple objects in a video. Most known algorithms are based on using simple detectors (e.g. YOLO) designed for processing individual images. The overall method involves separately using a detector on consecutive video frames and then matching the corresponding bounding boxes
The post The Hungarian Algorithm and Its Applications in Computer Vision appeared first on Towards Data Science.  Machine Learning, Artificial Intelligence, Computer Vision, Editors Pick, Hungarian Algorithm, Object Tracking Towards Data ScienceRead More