How does sort tracking algorithm work?

The Kalman filter operates by leveraging mathematical models and statistical principles to predict the state of a system given noisy measurements. In the context of Deep SORT, it forecasts the likely trajectories of moving objects.

The SORT algorithm serves as the cornerstone of Deep SORT, a sophisticated tracking system. It initiates its process by adopting a detection-centric methodology.

By predicting these trajectories, SORT can proactively adjust its associations based on actual measurements obtained from subsequent frames. This correction mechanism ensures that the tracking remains accurate and robust even in complex scenarios.

This approach involves meticulously examining consecutive frames to identify and associate objects that persist across these frames. By doing so, SORT establishes a foundational understanding of the dynamic environment.

Subsequently, the algorithm integrates a Kalman filter into its workflow. This powerful tool enables SORT to anticipate the future positions of the detected objects.