@inbook{5fab0879f8d6465089c7500a1c699d96,
title = "Inferring Leadership from Group Dynamics Using Markov Chain Monte Carlo Methods",
abstract = "This chapter presents a novel framework for identifying and tracking dominant agents in groups. The proposed approach relies on a causality detection scheme that is capable of ranking agents with respect to their contribution in recognizing the system's collective behavior 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 proposed scheme in identifying actual leaders in swarms of interacting agents and moving crowds.",
author = "Avishy Carmi and Lyudmila Mihaylova and Fran{\c c}ois Septier and Pang, {Sze Kim} and S.J. Godsill",
year = "2013",
doi = "10.1007/978-1-4614-8483-7_13",
language = "English",
isbn = "978-1-4614-8483-7",
volume = "11",
series = "The International Series in Video Computing",
publisher = "Springer New York",
pages = "325--346",
editor = "S. Ali and K. Nishino and D. Manocha and M. Shah",
booktitle = "Modeling, Simulation and Visual Analysis of Crowds",
address = "United States",
}