This work aims to evaluate people's perception regarding geometric features, personalities and emotions characteristics in virtual humans. For this, we use as a basis, a dataset containing the tracking files of pedestrians captured from spontaneous videos and visualized them as identical virtual humans. The goal is to focus on their behavior and not being distracted by other features. In addition to tracking files containing their positions, the dataset also contains pedestrian emotions and personalities detected using Computer Vision and Pattern Recognition techniques. We proceed with our analysis in order to answer the question if subjects can perceive geometric features as distances speeds as well as emotions and personalities in video sequences when pedestrians are represented by virtual humans. Regarding the participants, an amount of 73 people volunteered for the experiment. The analysis was divided in two parts: i) evaluation on perception of geometric characteristics, such as density, angular variation, distances and speeds, and ii) evaluation on personality and emotion perceptions. Results indicate that, even without explaining to the participants the concepts of each personality or emotion and how they were calculated (considering geometric characteristics), in most of the cases, participants perceived the personality and emotion expressed by the virtual agents, in accordance with the available ground truth.
@cite_9: The use of information technology in the study of human behavior is a subject of great scientific interest. Cultural and personality aspects are factors that influence how people interact with one another in a crowd. This paper presents a methodology to detect cultural characteristics of crowds in video sequences. Based on filmed sequences, pedestrians are detected, tracked and characterized. Such information is then used to find out cultural differences in those videos, based on the Big-five personality model. Regarding cultural differences of each country, results indicate that this model generates coherent information when compared to data provided in literature.
@cite_10: This article describes briefly the Hofstede model of six dimensions of national cultures: Power Distance, Uncertainty Avoidance, Individualism Collectivism, Masculinity Femininity, Long Short Term Orientation, and Indulgence Restraint. It shows the conceptual and research efforts that preceded it and led up to it, and once it had become a paradigm for comparing cultures, research efforts that followed and built on it. The article stresses that dimensions depend on the level of aggregation; it describes the six entirely different dimensions found in the (2010) research into organizational cultures. It warns against confusion with value differences at the individual level. It concludes with a look ahead in what the study of dimensions of national cultures and the position of countries on them may still bring. Creative Commons License This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. This article is available in Online Readings in Psychology and Culture: http: scholarworks.gvsu.edu orpc vol2 iss1 8
@cite_12: This paper presents a methodology to characterize information about groups of people with the main goal of detecting cultural aspects. Based on tracked pedestrians, groups are detected and characterized. Group information is then used to find out Cultural aspects in videos, based on the Hofstede cultural dimensions theory. The presented work was tested in videos of pedestrian groups recorded in different countries and results seem promising in order to identify cultural aspects in the filmed sequences.
@cite_20: The selection of adequate job candidates is very long and challenging process for each employer. The system presented in this paper is aiming to decrease the time for candidate selection on the pre-employment stage using automatic personality screening based on visual, audio and lexical cues from short video-clips. The system is build to predict candidate scores of 5 Big Personality Traits and to estimate a final decision, to which degree the person from video-clip has to be invited to the job interview. For each channel a set of relevant features is extracted, which are used to train separately from each other using Deep Learning. In the final stage all three results are fused together into final scores prediction. The experiment was conducted on first impression database and achieved significant performance.
@cite_11: Cultural behavior is an area of research that can allow us to further cross-cultural understanding, and is now starting to integrate itself within the field of information technology. One domain that expresses these behaviors is inside a crowd, however the analysis of micro-level crowd behavior is impractical in a real-world setting as passive observation has limitations on understanding true behavior. By using a virtual environment to simulate a crowd situation, measuring an individual's in-crowd behavior becomes feasible. This paper introduces the development of a virtual environment which enables the creation of different types of cultural crowds with which the user may interact. The parameterization of the crowds is based on the famous cultural dimensions put forward by Hofstede. One of the cultural dimensions, individualism collectivism, was mapped to agent characteristics during a series of simulations and it was found that two distinct types of crowd could be generated. For the dimensions have not yet been examined, the proposed environment provides an ideal opportunity to address this gap in the research as well as becoming a tool with which other types of experimentation can be performed.
Regarding the detection of personalities, emotion and cultural aspects in pedestrian from crowds, @cite_12 proposed a method to identify groups and characterize them to assess the aspects of cultural differences through the mapping of the Hofstede's dimensions @cite_10 . A similar idea, however using computer simulation and not focused on computer vision, is proposed by @cite_11 . They use Hofstede's dimensions to create a simulated crowd from a cultural perspective. Gorbova and collaborators @cite_20 present a system of automatic personality screening from video presentations in order to make a decision whether a person has to be invited to a job interview based on visual, audio and lexical cues. The work proposed by @cite_9 , presents a model to detect personality aspects based on the Big-five personality model using individuals behaviors automatically detected in video sequences.