Facial expressions contain emotionally expressive behaviour which is used to display emotional states. Every day many facial expressions are expressed, and these facial expressions need not be strictly specified due to the different surrounding and cultural background that each person has. Lot of research on the facial expression analysis has been done where focus is on the six basic emotional expressions (fear, anger, disgust, happiness, surprise and sadness). This paper focus on the use of facial expressions to recognize the basic six emotion state categories. Also, the goal of this approach is to extract the minimum number of facial feature vectors and reduce the dimensionality of the feature database to recognize emotion states. This paper includes experimentation results of homogeneous standard facial databases and heterogeneous facial databases. Also, a comparative analysis is discussed with state-of-the-art methods.Facial expressions contain emotionally expressive behaviour which is used to display emotional states. Every day many facial expressions are expressed, and these facial expressions need not be strictly specified due to the different surrounding and cultural background that each person has. Lot of research on the facial expression analysis has been done where focus is on the six basic emotional expressions (fear, anger, disgust, happiness, surprise and sadness). This paper focus on the use of facial expressions to recognize the basic six emotion state categories. Also, the goal of this approach is to extract the minimum number of facial feature vectors and reduce the dimensionality of the feature database to recognize emotion states. This paper includes experimentation results of homogeneous standard facial databases and heterogeneous facial databases. Also, a comparative analysis is discussed with state-of-the-art methods.
Volume 11 | Issue 1
Pages: 462-466