Classification of Indian Classical Dance Images using Convolution Neural Network
Ashwini Naik, M. Supriya
Abstract
Indian classical dance is the combination of gesture of all the body parts. It has varied forms and is generally a combination of single hand mudra, double hand mudra, leg alignment, hip movement, eye movement, facial expression, and leg posture. Each dance form has unique gesture, using which, they can be classified. The costumes worn by dancers are also unique. This work proposes the identification and classification of Indian Classical Dance images using Deep Learning Convolution Neural Network (CNN). This work uses the dataset consisting of five dance classes namely Bharatanatyam, Odissi, Kathak, Kathakali, Yakshagana, the images of which are collected from the internet using Google Crawler. This system can be used for automated dance quizzes and can be used by anyone to find out how well he/she is familiar with the variety of dance forms in India given its varied postures and styles.