Publication Type : Journal Article
Publisher : ICCSP
Source : 2020 International Conference on Communication and Signal Processing (ICCSP), p.1245-1249 (2020)
Campus : Bengaluru
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science
Year : 2016
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
Cite this Research Publication : A. Dayanand Naik and Dr. Supriya M., “Classification of Indian Classical Dance Images using Convolution Neural Network”, 2020 International Conference on Communication and Signal Processing (ICCSP), pp. 1245-1249, 2020.