In emergency situation, mass panic often causes more causalities than the disaster itself. The crowd emotional model could be used to simulate how crowd behavior in emergency scenarios and be helpful for developing crowd evacuation plans in emergency situations. However, existing crowd emotional models usually set model parameters in an empirical manner and are not validated by real cases. In this paper, a crowd emotional model is proposed to simulate the crowd movement in outdoor emergency situations. First of all, the crowd entropy and the movement difference are proposed to describe the emotional impact of the crowd scene on the agents. The perception of vision and hearing are considered, and the calculation formulas of the agent's emotional intensity and crowd emotional contagion are proposed. By calculating individual trajectories in the real video, the cumulative differences between the movements of the real crowd and the corresponding virtual crowd are analyzed. At last, a multi-parameter optimization method is implemented by the differential evolution algorithm. To verify the parameters in models, three videos which are generated from three real cases, including explosion attack, shooting incident, and crowd disturbance are selected for experimental verification. The results showed that the proposed model could be a feasible method for optimizing parameters to simulate the emergency scenario.

中文翻译：

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从突发事件视频中模拟人群情绪

在紧急情况下，群众恐慌往往比灾难本身造成更多的伤亡。人群情感模型可用于模拟紧急情况下人群的行为，有助于制定紧急情况下的人群疏散计划。然而，现有的人群情感模型通常以经验的方式设置模型参数，并没有得到真实案例的验证。在本文中，提出了一种人群情感模型来模拟户外紧急情况下的人群运动。首先，提出了人群熵和运动差异来描述人群场景对智能体的情感影响。考虑了视觉和听觉的感知，提出了智能体情绪强度和人群情绪传染的计算公式。通过计算真实视频中的个体轨迹，分析真实人群与相应虚拟人群运动的累积差异。最后通过差分进化算法实现了多参数优化方法。为了验证模型中的参数，选取爆炸袭击、枪击事件和人群扰动三个真实案例生成的三个视频进行实验验证。结果表明，所提出的模型是一种可行的参数优化方法来模拟紧急情况。为了验证模型中的参数，选取爆炸袭击、枪击事件和人群扰动三个真实案例生成的三个视频进行实验验证。结果表明，所提出的模型是一种可行的参数优化方法来模拟紧急情况。为了验证模型中的参数，选取爆炸袭击、枪击事件和人群扰动三个真实案例生成的三个视频进行实验验证。结果表明，所提出的模型是一种可行的参数优化方法来模拟紧急情况。