The Hungarian Algorithm and Its Applications in Computer Vision

Multi-object tracking (MOT) involves detecting and following objects across video frames, a task that requires matching corresponding detections. The Hungarian algorithm, an optimization method, is frequently used to solve this assignment problem by finding the most likely pairings. It operates on a cost matrix, such as one representing the distances between bounding boxes in consecutive frames, to find the assignment that minimizes the total cost. The algorithm iteratively transforms this matrix through row/column reduction and adjustment steps until an optimal solution, representing the correct object tracks, can be identified. This process provides a robust method for associating objects over time in computer vision applications.