Depth based Indian Classical Dance Mudra's Recognition using Support Vector Machine
D. Arpitha, M. Balasubrahmanyam, D. Anil Kumar
Abstract
I honorary present, an interesting application of Indian classical dance hasta mudra recognition as computer vision techniques. The dance mudras form a complex human gesture that are complicated to interpret by a machine. To solve this problem, I proposed a new framework for Indian classical dance recognition using depth sensor. First, the dance mudras of various classical dance datasets were created by using Microsoft Kinect (depth) sensor. Second, extract histogram of oriented (HOG) features of dance mudras as input of depth image and third, dance mudras are classified by using support vector machine (SVM) as converting dance mudras to text labels. The proposed framework tested by 50 dance mudras form different classical dance videos. To find the performance of proposed algorithm tested with different features and state-of-the-art methods.