This paper presents a robust single particle tracking (SPT) algorithm designed to address the challenges of high particle density, particle motion heterogeneity, temporary particle disappearance, and particle merging and splitting in live cell imaging. The algorithm uses the linear assignment problem (LAP) framework to link particles between consecutive frames and then link the resulting track segments into complete trajectories. Both steps are formulated as global combinatorial optimization problems to identify the most likely set of particle trajectories throughout the movie. The authors validate the algorithm through simulations and demonstrate its effectiveness in two applications: (1) accurate lifetime analysis of endocytic clathrin-coated pits (CCPs) and (2) single molecule tracking of CD36 receptors, revealing receptor aggregation and dissociation events. The results highlight the importance of robust and complete tracking in understanding the mechanisms of receptor organization at the plasma membrane.This paper presents a robust single particle tracking (SPT) algorithm designed to address the challenges of high particle density, particle motion heterogeneity, temporary particle disappearance, and particle merging and splitting in live cell imaging. The algorithm uses the linear assignment problem (LAP) framework to link particles between consecutive frames and then link the resulting track segments into complete trajectories. Both steps are formulated as global combinatorial optimization problems to identify the most likely set of particle trajectories throughout the movie. The authors validate the algorithm through simulations and demonstrate its effectiveness in two applications: (1) accurate lifetime analysis of endocytic clathrin-coated pits (CCPs) and (2) single molecule tracking of CD36 receptors, revealing receptor aggregation and dissociation events. The results highlight the importance of robust and complete tracking in understanding the mechanisms of receptor organization at the plasma membrane.