Affective laughter expressions from body movements

The main goal of this study is to classify affective laughter expressions from body movements. Using a non-intrusive Kinect sensor, body movement data from laughing participants were collected, annotated and segmented. A set of features that include the head, torso, shoulder movements, as well as the positions of the right and left hands, were used by a decision tree classifier to determine the type of emotions expressed in the laughter. The decision tree classifier performed with an accuracy of 71.02% using a minimum set of body movement features. © Springer International Publishing AG 2017