DHB: The Process of Collective Behavior: Validation of a Unified Mathematical Model Using Computer Vision Tracking

这个跨学科项目由一名社会心理学家、一名数学家、两名计算机科学家和一名社会学家组成，他们将集体行为的数学模型与用于图像跟踪、分类、模拟和动画的软件相结合。有待检验的假设是，与在个人或整个集体层面上运作的现有模型相反，大群体中的行为主要是由小团体内部和小团体之间的社会影响造成的。该模型统一了这些方法，并允许通过改变个体因素与整个集体属性的重要性以及小团体相互作用的影响来进行比较评估。该模型的验证将基于对不同性质、结构和大小的人群视频的新型计算机视觉分析。本项目将开发的理论和工具可协助执法、应急管理和事件管理人员尽量减少暴力、加快疏散和减少意外伤害。自动跟踪软件将提供远远超出人类观察者所能准确判断的实时信息。

This interdisciplinary project teams a social psychologist, a mathematician, two computer scientists, and a sociologist in research that combines a mathematical model of collective behavior with software for image tracking, classification, simulation, and animation. The hypothesis to be tested is that behavior in a large crowd results primarily from social influence within and between small groups, in contrast to existing models, which operate at the level of the individual or of the entire collective. The model unifies these approaches and allows for comparative assessment by varying the importance given to individual factors versus properties of the entire collective versus the influence of small-group interaction. Validation of the model will be based on novel computer vision analyses of videos of crowds of varying nature, structure, and size. The theory and the tools to be developed by this project can assist personnel in law enforcement, emergency management, and event management to minimize violence, speed up evacuations, and reduce accidental injury. The automated tracking software will provide real-time information far beyond what human observers can accurately determine.