This paper presents a study, organized in two phases, regarding group behavior in a controlled experiment focused on differences in an important attribute that vary across cultures—personal spaces. First, we want to study and compare the spatial behavior different populations adopt with respect to their personal space. Second, we want to use simulation of virtual agents to artificially generate movements of people in similar situations and validate them using real video sequences. Our main goal is to be able to extract from video sequences and then simulate variations in populations in a coherent way with literature that studies cultural aspects. In addition to the cultural aspects, we also investigate the personality model in the studied videos using OCEAN (Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism). Finally, we propose a way to simulate the fundamental diagram experiment from other countries using the OCEAN psychological trait model as input. Results indicate that the simulated countries have consistent characteristics with the expected literature.

This paper presents a study regarding group behavior in a controlled experiment focused on differences in an important attribute that vary across cultures -the personal spaces -in two Countries: Brazil and Germany. In order to coherently compare Germany and Brazil evolutions with same population applying same task, we performed the pedestrian Fundamental Diagram experiment in Brazil, as performed in Germany. We use convolutional neural networks to detect and track people in video sequences. With this data, we use Voronoi Diagrams to find out the neighbor relation among people and then compute the walking distances to find out the personal spaces. Based on personal spaces analyses, we found out that people behavior is more similar in high dense populations. So, we focused our study on cultural differences between the two Countries in low and medium densities. Results indicate that personal space analyses can be a relevant feature in order to understand cultural aspects in video sequences even when compared with data from self-reported questionnaires.