A vertical-horizontal-intersections feature based method for identification of bharatanatyam double hand mudra images

  title={A vertical-horizontal-intersections feature based method for identification of bharatanatyam double hand mudra images},
  author={Basavaraj S. Anami and Venkatesh Arjunasa Bhandage},
  journal={Multimedia Tools and Applications},
Bharatanatyam is an Indian classical dance, which has to be studied under an expert. [] Key Method In the first stage, acquired images of Bharatanatyam mudras are preprocessed to obtain contours of mudras using canny edge detector. In the second stage, cell features are extracted that include number of vertical and horizontal intersections of grid lines with the contours of the mudras. In the third stage, a rule based classifier is developed to classify the given image into 24 classes of mudras.
4 Citations
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Unravelling of Convolutional Neural Networks through Bharatanatyam Mudra Classification with Limited Data
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Transfer Learning for Classifying Single Hand Gestures on Comprehensive Bharatanatyam Mudra Dataset
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This paper presents a method for automatic hand gesture recognition of 'Bharatanatyam' dance using Fuzzy L membership function based approach and gives overall an accuracy of 85.1% and timing complexity is 2.563 sec in an Intel Pentium Dual Core processor running Mat lab R011b.
Recognizing Bharatnatyam Mudra Using Principles of Gesture Recognition
A novel approach of computer aided recognition of Bharatnatyam Mudras is proposed using the saliency technique which uses the hypercomplex representation of the image to highlight the object from background and in order to get the salient features of the static double hand mudra image.
Indian Classical Dance Mudra Classification Using HOG Features and SVM Classifier
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