Abstract
Communication plays a pivotal role in every person’s life.There are various types of communications in which some are verbal and some are non-verbal. Expressions on a person’s face are a type of non-verbal communication.Expressions on the face can be used to define how the person is feeling, recognizing them helps to enhance the human-machine interaction.Thus we propose a system that is un-affected by the illumination changes or the light changes. Expressions on the human face can be computed by using CLM,constrained local models inserts a dense model to a new input image to get the emotions stats .SVM classifier is used to distinguish the input image into different emotion categories. Results showed a remarkable increase in efficiency and performance. Change in lighting conditions will have a very little effect on the efficiency of the system.
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