Facial Expression Recognition From Incomplete Information
Details
The author tried facial expression identification in supposed state, that some part of the face is hidden, especially the nose and the mouth is hidden by the mask. 8 feature points around the eyes were extracted by using Active Appearance Models. The author defined feature values as square of the distance between the feature points, and angle. Machine learning was carried out by Support Vector Machine based on the feature value. The recall was 37.58% and the precision was 37.12%.
