Evolução das posturas corporais de estudantes em apresentações de seminários ao longo do semestre: uma análise utilizando dados multimodais e técnicas de clusterização

Abstract

The present paper describes a clustering based approach to identify the main corporal patterns in students oral presentations during a given course. Data from 43 students presentations was collected through the use ofMicrosoft Kinect. The 16 collected features were used as input information in the cluste- rization process allowing the identification ofthree main profiles ofpresenters: passive, active, and semi-active. An analysis of the evolution of these profiles during the semester points out a decrease in the percentage of the passive pro- file throughout the course, and an increase in the percentage ofthe semi-active profile. These different profiles will be integrated into the system that collects the postures information in order to allow the automated classification of the presenters in real time.