Virtual crowds are a prominent feature for a range of applications; from simulations for cultural heritage, to interactive elements in video games. A body of existing research seeks to develop and improve algorithms for crowd simulation, typically with a goal of achieving more realistic behaviours. For applications targeting human interaction however, what is judged as realistic crowd behaviour can be subjective, leading to situations where actual crowd data is not always perceived to be more real than simulation, making it difficult to identify a ground truth. We present a novel method using psychophysics to assess the perceived realism of behavioural features with respect to virtual crowds. In this instance, a focus is given to the grouping dynamics feature, whereby crowd composition in terms of group frequency and density is evaluated through thirty-six conditions based on crowd data captured from three pedestrianised real-world locations. The study, conducted with seventy-eight healthy participants, allowed for the calculation of perceptual thresholds, with configurations identified that appear most real to human viewers. The majority of these configurations correlate with the values extracted from the crowd data, with results suggesting that viewers have more perceptual flexibility when group frequency and density are increased, rather than decreased.

虚拟人群是许多应用程序的显着特征。从文化遗产模拟到视频游戏中的互动元素。现有的大量研究旨在开发和改进用于人群仿真的算法，通常目的是实现更逼真的行为。但是，对于面向人类交互的应用程序，被认为是现实的人群行为可能是主观的，从而导致实际的人群数据并不总是比模拟更真实，从而难以识别基本事实。我们提出一种使用心理物理学来评估虚拟人群行为特征感知现实的新颖方法。在这种情况下，重点放在分组动态功能上，从而根据从三个行人专用现实位置捕获的人群数据，通过三十六个条件评估人群构成和频率。该研究由78位健康参与者进行，可以计算感知阈值，并确定对人类观众来说最真实的配置。这些配置中的大多数与从人群数据中提取的值相关，结果表明，当组频率和密度增加而不是减少时，观看者具有更大的感知灵活性。确定了对人类观看者来说最真实的配置。这些配置中的大多数与从人群数据中提取的值相关，结果表明，当组频率和密度增加而不是减少时，观看者具有更大的感知灵活性。确定了对人类观看者来说最真实的配置。这些配置中的大多数与从人群数据中提取的值相关，结果表明，当组频率和密度增加而不是减少时，观看者具有更大的感知灵活性。