Descriptive Analysis of Human Emotions Based on Eye pupils
Facial emotional expressions are viewed as the most descriptive way to understand the human’s state of temperament during confronting communication. In this work numerous statistical approaches have been applied on human eye pupil with static images of Chicago face dataset (CFD) to analyze and classify the considered categories for emotions which are Happy, Fear, Anger and Neutral. The aim of this study is to develop the specific architecture for image processing domain after applying different enhancement techniques on human eye pupil for analysis & recognition of the facial expressions. This work is divided into three phases initially in the first phase data preprocessing is performed to prepare according to the requirement of work and also the color images are converted in to negative by applying the pixel intensity controlled mechanism. Second phase define the boundary to compute the feature by using Circular Hough Transform algorithm. Lastly statistical approaches are applied on extracted features to corporate the central point of pupil. This corporation the central point presents the effects of emotions. While comparing peoples of different Age groups it is concluded that pupil constricted on Anger at different levels on different age groups. If further it is discussed about cross cultural and gender wise comparison then Happy Emotion effects most and resulted towards dilated pupil same like that Anger emotion effects most on constricting the pupil size.