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Classification of Indian Classical Dance Images using Convolution Neural Network

Publication Type : Journal Article

Publisher : 2020 International Conference on Communication and Signal Processing (ICCSP)

Source : 2020 International Conference on Communication and Signal Processing (ICCSP), p.1245-1249 (2020)

Url : https://www.semanticscholar.org/paper/Classification-of-Indian-Classical-Dance-Images-Naik-Supriya/4af5157029c502d79dd75cad5dd5746f13dc3f07

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.

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