Features extraction for facial expressions recognition

The recognition of an expression seems obvious and easy when classified by the human brain. However, it is clearly difficult for a computer to detect human face, extract all of the components characterizing the facial expression and then determine its classification from a single image. Moreover, based on videos, the process becomes even more complex because it must take simultaneously into account the temporal and spatial information available. Also, It should be noted that facial features have an important fact to developing a robust face representation because it aims to select the best of features and reduce dimensionality of features set by finding a new set which contains most of the face features information. For those reasons, this paper present several features extraction approaches for facial expressions recognition as state-of-the-art review.