Automatic expression recognition and expertise prediction in Bharatnatyam

Abstract

Bharatnatyam is an ancient Indian Classical Dance form consisting of complex postures and expressions. One of the main challenges in this dance form is to perform expression recognition and use the resulting data to predict the expertise of a test dancer. In this paper, expression recognition is carried out for the 6 basic expressions in Bharatnatyam using iMotions tool. The intensity values obtained from this tool for 4 distinct expressions - Joy, Surprise, Sad and Disgust are being used as our feature set for classification and predictive analysis. The recognition was performed on our own dataset consisting of 50 dancers with varied expertise ratings. Logistic Regression performed the best for Joy, Surprise and Disgust expressions giving an average accuracy of 80.78% whereas Support Vector Machine classifier with Radial Basis kernel function performed best for Sad expression giving an accuracy of 71.36%. A separate analysis on positive and negative emotions is carried out to determine the expertise of each rating on the basis of these emotions.