MCMC-Based Tracking and Identification of Leaders in Groups

Abstract : We present a novel framework for identifying and track- ing dominant agents in groups. Our proposed approach relies on a causality detection scheme that is capable of ranking agents with respect to their contribution in shap- ing the system's collective behaviour based exclusively on the agents' observed trajectories. Further, the reasoning paradigm is made robust to multiple emissions and clutter by employing a class of recently introduced Markov chain Monte Carlo-based group tracking methods. Examples are provided that demonstrate the strong potential of the pro- posed scheme in identifying actual leaders in swarms of in- teracting agents and moving crowds.