Modeling Trajectory-level Behaviors using Time Varying Pedestrian Movement Dynamics

Aniket Bera, Sujeong Kim, Dinesh Manocha
2018 Collective Dynamics  
We present a novel interactive multi-agent simulation algorithm to model pedestrian movement dynamics. We use statistical techniques to compute the movement patterns and motion dynamics from 2D trajectories extracted from crowd videos. Our formulation extracts the dynamic behavior features of real-world agents and uses them to learn movement characteristics on the fly. The learned behaviors are used to generate plausible trajectories of virtual agents as well as for long-term pedestrian
more » ... ry prediction. Our approach can be integrated with any trajectory extraction method, including manual tracking, sensors, and online tracking methods. We highlight the benefits of our approach on many indoor and outdoor scenarios with noisy, sparsely sampled trajectory in terms of trajectory prediction and data-driven pedestrian simulation.
doi:10.17815/cd.2018.15 fatcat:i74i7bbap5fcfez5nexgt7l3tm