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Indian Classical Dance Mudra Classification Using HOG Features and SVM Classifier

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Smart Computing and Informatics

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 77))

Abstract

Digital understanding of Indian classical dance is least studied work, though it has been a part of Indian Culture from around 200 BC. This work explores the possibilities of recognizing classical dance mudras in various dance forms in India. The images of hand mudras of various classical dances are collected from the internet, and a database is created for this job. Histogram of oriented (HOG) features of hand mudras input the classifier. Support vector machine (SVM) classifies the HOG features into mudras as text messages. The mudra recognition frequency (MRF) is calculated for each mudra using graphical user interface (GUI) developed from the model. Popular feature vectors such as SIFT, SURF, LBP, and HAAR are tested against HOG for precision and swiftness. This work helps new learners and dance enthusiastic people to learn and understand dance forms and related information on their mobile devices.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, K L University, Green Fields, Vaddeswaram, Guntur District, Andhra Pradesh, India

    K. V. V. Kumar & P. V. V. Kishore

Authors
  1. K. V. V. Kumar
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  2. P. V. V. Kishore
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Correspondence to K. V. V. Kumar .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, PVP Siddhartha Institute of Technology, Vijayawada, Andhra Pradesh, India

    Suresh Chandra Satapathy

  2. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  3. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Swagatam Das

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Kumar, K.V.V., Kishore, P.V.V. (2018). Indian Classical Dance Mudra Classification Using HOG Features and SVM Classifier. In: Satapathy, S., Bhateja, V., Das, S. (eds) Smart Computing and Informatics . Smart Innovation, Systems and Technologies, vol 77. Springer, Singapore. https://doi.org/10.1007/978-981-10-5544-7_65

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  • DOI: https://doi.org/10.1007/978-981-10-5544-7_65

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-5543-0

  • Online ISBN: 978-981-10-5544-7

  • eBook Packages: EngineeringEngineering (R0)

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