Representations for facial expressions

Non-manual signals (NMS) are grammatical elements in sign languages. They may convey information that reinforces or is additional to the hand signing. NMS are similar to facial expressions except that, unlike spontaneous emotions, NMS are deliberate gestures. This paper explores the use of Independent Component Analysis (ICA) and Gabor wavelet networks (GWNs) for recognising 3 upper face and 3 lower face expressions related to NMS. Independent component analysis and Gabor wavelet networks were compared as representations for these facial signals. Both representations provided good recognition performance. The method of using GWNs with 116 wavelets outperformed ICA (85.3% and 93.3% for upper and lower face respectively, compared to 78.7% and 92% for ICA). However, the GWN method is computationally more expensive.