A Software to Detect OCC Emotion, Big-Five Personality and Hofstede Cultural Dimensions of Pedestrians from Video Sequences

Autor:	Favaretto, Rodolfo Migon, Araujo, Victor, Musse, Soraia Raupp, Vilanova, Felipe, Costa, Angelo Brandelli
Rok vydání:	2019
Předmět:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Human-Computer Interaction
Druh dokumentu:	Working Paper
Popis:	This paper presents a video analysis application to detect personality, emotion and cultural aspects from pedestrians in video sequences, along with a visualizer of features. The proposed model considers a series of characteristics of the pedestrians and the crowd, such as number and size of groups, distances, speeds, among others, and performs the mapping of these characteristics in personalities, emotions and cultural aspects, considering the Cultural Dimensions of Hofstede (HCD), the Big-Five Personality Model (OCEAN) and the OCC Emotional Model. The main hypothesis is that there is a relationship between so-called intrinsic human variables (such as emotion) and the way people behave in space and time. The software was tested in a set of videos from different countries and results seem promising in order to identify these three different levels of psychological traits in the filmed sequences. In addition, the data of the people present in the videos can be seen in a crowd viewer. Comment: 13 pages, 9 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1908.06484 Zobrazit plný text záznamu View this record from Arxiv