@misc{cogprints3349, volume = {101}, editor = {Christopher G. Prince and Luc Berthouze and Hideki Kozima and Daniel Bullock and Georgi Stojanov and Christian Balkenius}, title = {Towards Learning Affective Body Gesture}, author = {Andrea Kleinsmith and Nadia Bianchi-Berthouze}, publisher = {Lund University Cognitive Studies}, year = {2003}, pages = {169--170}, keywords = {gesture recognition, affect recognition, robot-human communication, Categorizing and Learning modules}, url = {http://cogprints.org/3349/}, abstract = {Robots are assuming an increasingly important role in our society. They now become pets and help support children healing. In other words, they are now trying to entertain an active and affective communication with human agents. However, up to now, such systems have primarily relied on the human agents' ability to empathize with the system. Changes in the behavior of the system could therefore reult in changes of mood or behavior in the human partner. This paper describes experiments we carried out to study the importance of body language in affective communication. The results of the experiments led us to develop a system that can incrementally learn to recognize affective messages conveyed by body postures.} }