Title: SME feature-based classification of Adavu and posture images of Bharatanatyam dance
Authors: Basavaraj S. Anami; Venkatesh Arjunasa Bhandage
Addresses: K.L.E. Institute of Technology, Hubballi-Karnataka, India ' Department of CSE, Tontadarya College of Engineering, Gadag-Karnataka, India
Abstract: The Adavus are typical and fundamental postures in Bharatanatyam dance. Adavu is a predefined sequence of hands, legs and neck with pre-set body pose forms, which are studied under the guidance of experts, who are becoming scarce in these days. This paper proposes a three-stage approach for classification of Adavu images. In the first stage, contours of Adavus are obtained. In the second stage, the structural(S), moments(M) and eigen values(E) features, namely, intersections, symmetric property, width_height_difference, contour distance, Hu-moments and eigenvalues are obtained. ANN is used for classification of Adavus in third stage. A comparative study of classification accuracies of using different features is made. The envisaged applications of this research include e-learning of Adavus and Bharatanatyam dance, in particular, and various dances, in general, evaluation of Adavus exhibited by a performer for their accuracies, and automation of commentary during the concerts and the like.
Keywords: Bharatanatyam; Adavu; contour of Adavu; intersections; symmetric property; contour distance; width_height_difference; Hu-moments; eigenvalues; artificial neural network.
International Journal of Arts and Technology, 2020 Vol.12 No.4, pp.317 - 334
Received: 01 Dec 2019
Accepted: 03 Sep 2020
Published online: 25 Jan 2021 *