Facial Expression Recognition using Facial Features Detection using the Fusion of Classifiers: In a real-time scenario

For the communication, there are two modes of communication i.e. verbal and non-verbal. The speech is the medium of verbal communication whenever the gestures and the facial expressions are the medium of non-verbal communication. In our daily social life, the facial expressions play an important role to convey some information between the speaker and the listener. The facial expressions can not only change the flow of conversation but also provide some contextual information to the listener, therefore, the listener can easily sense the actual state of the convener. Facial expression express human's inner emotional states. In this paper, an approach has been proposed to detect the specific region of the face which consist of very high information for emotion recognition. In this work, the approach is to detect some particular region of the face instead to detect all facial parts. Therefore this approach is faster than the existing approaches for facial expression recognition. For the classification, a fusion approach has been used and achieved a good recognition rate with the combination of HOG and LBP features.