Facial expression recognition using string grammar fuzzy K-nearest neighbor

• Main Authors: Kasemsumran P., Auephanwiriyakul S., Theera-Umpon N.
• Format: Book Series
• Published: 2017
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84978818959&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/42248
• Institution: Chiang Mai University

© Springer International Publishing Switzerland 2016. Facial expression recognition can provide rich emotional information for human computer interaction. It has become more and more interesting problem recently. Therefore, we propose a facial expression recognition system using the string grammar fuzzy K-nearest neighbor. We test our algorithm on 3 data sets, i.e., the Japanese Female Facial Expression (JAFFE), the Yale, and the Project- Face In Action (FIA) Face Video Database, AMP, CMU (CMU AMP) face expression databases. The system yields 89.67 %, 61.80 %, and 96.82 % in JAFFE, Yale and CMU AMP, respectively. We compare our results indirectly with the existing algorithms as well. We consider that our algorithm provides comparable results with those existing algorithms but we do not need to crop an image beforehand.