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Detecting personality and emotion traits in crowds from video sequences

  • Rodolfo Migon FavarettoEmail author
  • Paulo Knob
  • Soraia Raupp Musse
  • Felipe Vilanova
  • Ângelo Brandelli Costa
Special Issue Paper

Abstract

This paper presents a methodology to detect personality and basic emotion characteristics of crowds in video sequences. Firstly, individuals are detected and tracked, and 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.

Keywords

Computer vision Crowd features Big Five model Cultural dimensions Crowd emotion 

Supplementary material

138_2018_979_MOESM1_ESM.mp4 (138.7 mb)
Supplementary material 1 (mp4 142068 KB)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.VHLab, Graduate Program in Computer SciencePUCRSPorto AlegreBrazil
  2. 2.Graduate Program in PsychologyPUCRSPorto AlegreBrazil

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