Automatic recognition of affective laughter from body movements

• Main Authors: Luz, Ma. Beatrice L, Nocum, McAnjelo D., Purganan, Timothy Jasper T., Timothy, Jasper T., Wong, Wing San T.
• Format: text
• Language: English
• Published: Animo Repository 2015
• Subjects: Optical pattern recognition; Facial expression; Laughter; Philippine wit and humor; Computer Sciences
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/11106
• Institution: De La Salle University

Laughter is often associated with happiness but recent studies show that there are actually five types of Filipino laughter and these are happiness, giddiness, excitement, embarrassment, and hurtful laughter. Facial expressions and vocalization related to laughter have been the focus in many studies however body movements are still unexplored. This research will make use of the Microsoft Kinect for detecting body movements. High-level feature extraction will be applied in order to translate the points gathered through the Microsoft Kinect into a more understandable data. This research aims to classify these types of laughter with the use of one modality which is the body movements. The researchers will determine which specific body parts are important to track in order to determine the type of laughter through feature selection. With the use of different machine learning techniques, this research aims to build a model that would classify which type of laughter is being performed.