Martin Jordan, Hoyet Ludovic, Pinsard Etienne, Paillat Jean-Luc, Pettre Julien
IEEE Trans Vis Comput Graph. 2024 Nov;30(11):7008-7019. doi: 10.1109/TVCG.2024.3456183. Epub 2024 Oct 10.
Crowd data is a crucial element in the modeling of collective behaviors, and opens the way to simulation for their study or prediction. Given the difficulty of acquiring such data, virtual reality is useful for simplifying experimental processes and opening up new experimental opportunities. This comes at the cost of the need to assess the biases introduced by the use of this technology. Our paper is part of this effort, and investigates the effect of the graphical representation of a crowd on the behavior of a user immersed within. More specifically, we inspect the virtual navigation through virtual crowds, in terms of travel speeds and local navigation choices as a function of the visual representation of the virtual agents that make up the crowd (simple geometric model, anthropomorphic model or realistic model). Through an experiment in which we ask a user to navigate virtual crowds of varying densities, we show that the effect of the visual representation is limited, but that an anthropomorphic representation offers the best trade-off between computational complexity and ecological validity, even though a more realistic representation can be preferred when user behaviour is studied in more details. Our work leads to clear recommendations on the design of immersive simulations for the study of crowd behavior.
群体数据是集体行为建模中的关键要素,为研究或预测集体行为的模拟开辟了道路。鉴于获取此类数据的困难,虚拟现实有助于简化实验过程并开辟新的实验机会。但这样做的代价是需要评估使用该技术所引入的偏差。我们的论文是这项工作的一部分,研究了人群的图形表示对沉浸其中的用户行为的影响。更具体地说,我们根据构成人群的虚拟代理的视觉表示(简单几何模型、拟人模型或真实模型),从行进速度和局部导航选择方面考察通过虚拟人群的虚拟导航。通过一项实验,我们让用户在不同密度的虚拟人群中导航,结果表明视觉表示的影响是有限的,不过拟人化表示在计算复杂性和生态有效性之间提供了最佳平衡,尽管在更详细地研究用户行为时,可能会更倾向于更真实的表示。我们的工作为研究人群行为的沉浸式模拟设计提供了明确的建议。