Gesture-based affect modeling for intelligent tutoring systems - Bustos, Dana May (Animo Repository, 2011)
This paper investigates the feasibility of using gestures and posture for building affect models for an ITS. Recordings of students studying with a computer were taken and an HMM was built to recognize gestures and posture. Results indicate distinctions can be achieved with an accuracy of 43.10% using leave-one out cross validation. Results further indicate the relevance of hand location, movement and speed of movement as features for affect modeling using gestures and posture. © 2011 Springer-Verlag Berlin Heidelberg.