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MCMC-Based Tracking and Identification of Leaders in Groups

Research output: Contribution in Book/Report/ProceedingsPaper

Published

Publication date7/11/2011
Host publicationIEEE International Conference on Computer Vision Workshops (ICCV Workshops), 2011
PublisherIEEE
Pages112-119
Number of pages8
ISBN (Print)978-1-4673-0062-9
Original languageEnglish

Conference

ConferenceEEE Workshop on Modeling, Simulation and Visual Analysis of Large Crowds
CountrySpain
CityBarcelona
Period6/11/1113/11/11

Conference

ConferenceEEE Workshop on Modeling, Simulation and Visual Analysis of Large Crowds
CountrySpain
CityBarcelona
Period6/11/1113/11/11

Abstract

We present a novel framework for identifying and tracking 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 shaping 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 proposed scheme in identifying actual leaders in swarms of interacting agents and moving crowds.