Multiple object tracking is a core research area focused on the computational process of identifying multiple distinct objects within temporal sequences of visual data and maintaining their identities and estimating their trajectories over time. This field investigates algorithms and methodologies for robust object detection, data association across frames, and trajectory estimation, addressing challenges such as occlusion, clutter, and object interactions, and is fundamental for applications requiring the analysis and understanding of dynamic visual scenes.