This paper presents a methodology to detect personality and basic emotion characteristics of crowds in video sequences. Firstly, individuals are detected and tracked, then groups are recognized and characterized. Such information is then mapped to OCEAN dimensions, used to find out personality and emotion in videos, based on OCC emotion models. Although it is a clear challenge to validate our results with real life experiments, we evaluate our method with the available literature information regarding OCEAN values of different Countries and also emergent Personal distance among people. Hence, such analysis refer to cultural differences of each country too. Our results indicate that this model generates coherent information when compared to data provided in available literature, as shown in qualitative and quantitative results.

翻译：本文介绍了在视频序列中检测人群的个性和基本情感特征的方法。首先,对个人进行检测和跟踪,然后对群体进行识别和定性。然后,根据OCC的情感模式,将这些信息绘制成OCEAN维度,用于在视频中发现个性和情感。虽然通过现实生活实验来验证我们的结果是一个明显的挑战,但我们还是用关于不同国家OCEAN价值观的现有文献信息来评估我们的方法,以及人们之间新出现的个人距离。因此,这种分析也涉及每个国家的文化差异。我们的结果表明,与现有文献中提供的数据相比,这一模式产生了一致的信息,如定性和定量结果所示。