Multi-Ocular Laban Movement Analysis of Emotional Characteristics

It is presented in the paper, a contribution to the field of human-machine interaction a system that has the ability to analyze emotional content of human movements, using as basis a technique known as Laban Movement Analysis. This work searches for computational approaches to quantify human qualities like emotion and expression and explores new functionalities towards implementation of more advanced surveillance systems or perception system for social robots. Human body parts are tracked using both vision and magnetic trackers, generating trajectories. Laban Analysis concept is used to extract useful features from those trajectories to classify human movements. To solve the problem of classification a Bayesian framework was adopted, as it offers an intuitive approach to learning and classification. The descriptor opens a wide range of possibilities to analyze the emotional content and expressiveness of gestures.