Fusion of features for the effective facial expression recognition

Facial Expression is the easy way of telling/showing inner feelings. The Facial Expression Recognition system has many applications including human behavior understanding, detection of mental disorders, synthetic human expressions and many more. This paper presents a quick survey of facial expression recognition as well as a comparative study of various features on JAFFE and CK datasets. It mainly focuses on appearance based techniques. Recently, HOG has been widely used for feature extraction in image. It is found in our experiment that HOG feature gives comparable good recognition rate in facial expression recognition. Fusion of LBP with LGC and Fusion of HOG with other features like LDP and wavelets also improved their respective recognition rates.