3D measures and geometric facial features analysis on 3D facial action unit recognition

• Main Authors: Hamimah, Ujir, Cecilia, Assan, Irwandi Hipni, Mohamad Hipiny, Dayang Nurfatimah, F Awang Iskandar
• Format: Article
• Language: English
• Published: American Scientific Publishers 2015
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://ir.unimas.my/id/eprint/15201/1/3D-measures-and-geometric-facial-features-analysis-on-3D-facial-action-unit-recognition_2015_Advanced-Science-Letters.html; http://ir.unimas.my/id/eprint/15201/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961275677&doi=10.1166%2fasl.2015.6564&partnerID=40&md5=9ea10ddf37adcbc1a2a9c8ac5996dc37

We constructed a statistical model for variations in facial shape due to differences in 22 facial action units (AUs) using three different 3D measures and geometric facial features as the feature vectors. The three facial features are 3D facial points, 3D facial surface normals and 3D distance measurements. Finally, we apply Support Vector Machines as the classifier and 10-fold cross validation are performed on the Bosphorus database. Using our approach, 3D facial points yields a better performance than 3D facial distance measurements and 3D facial surface normal in 3D Facial AU recognition.