Simulating realistic crowd based on agent trajectories
This paper presents a model for simulating realistic crowd behaviors at low computation cost. The proposed model is inspired by video data. In our approach, we first classify the crowd into two categories: main and background characters. Whether the agents are main characters or not is influenced by two factors, one is the agent's trajectories and the other one is the change of the environment. In the second stage, we adopt two approaches to simulate the behaviors of main and background characters. Main characters are intelligent agents with the perception, the memory, the planning, and the psychology so that they can make decisions themselves. Background characters are informed of the behavior options for execution by the smart environment. Finally, we simulate the road-crossing scenario in a three-dimensional virtual environment. The experimental results demonstrate that our approach not only well reflects the characteristics of agent behaviors but also reduces the computation complexity of simulating realistic crowd. Copyright (c) 2013 John Wiley & Sons, Ltd.
agent trajectory background characters main characters crowd simulation svm classifier