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

Resumo

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 of Microsoft Kinect. The 16 collected features were used as input information in the clusterization process allowing the identification of three main profiles of presenters: 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 profile throughout the course, and an increase in the percentage of the 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.