New distances combination for facial expression recognition from image sequences
Fatima Zahra Salmam, Abdellah Madani, Mohamed Kissi · 2016
This paper propose a new method of facial expression recognition from image sequences taking into consideration only the first and the last frames, that represent respectively the neutral state and the emotion state. Our proposed method is based on calculating six distances from eleven points of the face. These points are detected and tracked using supervised decent method, and refer to the four internal parts of the face (eyebrows, eyes, nose, and mouth). After that, two data mining techniques are used to classify facial expression into emotion, taking as input dynamic feature vector deducted from the six distances previously calculated in the first and the last frames. Our method achieved a best recognition rate of 98% in the CK+ database, and 80.6% in the OULU-CASIA VIS database.