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

## TL;DR

This paper introduces a video analysis software that detects pedestrians' emotions, personality traits, and cultural dimensions from video sequences, aiming to understand human behavior in public spaces.

## Contribution

It presents a novel model that maps pedestrian characteristics to psychological and cultural traits using visual data and established psychological models.

## Key findings

- Promising results in identifying psychological traits from videos
- Effective visualization of crowd psychological profiles
- Model applicable across different cultural contexts

## Abstract

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.