Abstract
Group members have different attitudes and behavioural patterns that can be characterized using behavior analysis. Group managers and leaders at work, school, college and healthcare facilities are obligated to understand Group Dynamics in order to form the right productive team. In this research, we study the feasibility of automatically analyzing an individual's behavior during an interaction setting using body language cues, in order to determine their best role in a team context. We approach this issue by obtaining non-verbal cues and using them as indicators to assess the widely used Big-Five personality traits. Our aim is to build a Decision Support System (DSS) that assists group and team leaders in allocating the members' roles according to their behavioral characteristics. With the advancement on affective computing technologies, we believe that our work could achieve high performance accuracies that could then result in a generalized method to be later adopted in other relevant contexts.