Skip to main content
SpringerLink
Log in
Book cover

Proceedings of International Conference on Computer Vision and Image Processing pp 581–591Cite as

Using Musical Beats to Segment Videos of Bharatanatyam Adavus

  • Conference paper
  • First Online:

  • 1207 Accesses

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 459))

Abstract

We present an algorithm for audio-guided segmentation of the Kinect videos of Adavus in Bharatanatyam dance. Adavus are basic choreographic units of a dance sequence in Bharatanatyam. An Adavu is accompanied by percussion instruments (Tatta Palahai (wooden stick)—Tatta Kozhi (wooden block), Mridangam, Nagaswaram, Flute, Violin, or Veena) and vocal music. It is a combination of events that are either postures or small movements synchronized with rhythmic pattern of beats or Taals. We segment the videos of Adavus according to the percussion beats to determine the events for recognition of Adavus later. We use Blind Source Separation to isolate the instrumental sound from the vocal. Beats are tracked by onset detection to determine the instants in the video where the dancer assumes key postures. We also build a visualizer for test. From over 13000 input frames of 15 Adavus, 74 of the 131 key frames actually present get detected. Every detected key frame is correct. Hence, the system has 100 % precision, but only about 56 % recall.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    Short-Time Fourier Transform.

References

  1. Alexey Ozerov, Emmanuel Vincent, and Frdric Bimbot. A general flexible framework for the handling of prior information in audio source separation. Audio, Speech, and Language Processing, IEEE Transactions on, 20, 2012.

    Google Scholar 

  2. Yun Li, K. C. Ho, and Mihail Popescu. A general flexible framework for the handling of prior information in audio source separation. Biomedical Engineering, IEEE Transactions on, 61, 2014.

    Google Scholar 

  3. Daniel P.W. Ellis. Beat tracking by dynamic programming. Journal of New Music Research, 36, 2007.

    Google Scholar 

  4. Jonathan T. Foote and Matthew L. Cooper. Visualizing musical structure and rhythm via self-similarity. In MULTIMEDIA ’99 Proceedings of the seventh ACM international conference on Multimedia, pages 77–80, 1999.

    Google Scholar 

  5. Jonathan T. Foote and Matthew L. Cooper. Media segmentation using self-similarity decomposition. In Proc. SPIE Storage and Retrieval for Media Databases, 2003.

    Google Scholar 

  6. Zafar Rafii and Bryan Pardo. Repeating pattern extraction technique (repet): A simple method for music/voice separation. Audio, Speech, and Language Processing, IEEE Transactions on, 21, 2012.

    Google Scholar 

  7. Ajay Srinivasamurthy, Gregoire Tronel, Sidharth Subramanian, and Parag Chordia. A beat tracking approach to complete description of rhythm in indian classical music. In 2nd CompMusic Workshop, 2012.

    Google Scholar 

  8. Juan Pablo Bello, Laurent Daudet, Samer Abdallah, Chris Duxbury, Mike Davies, and Mark B. Sandler. A tutorial on onset detection in music signals. Speech and Audio Processing, IEEE Transactions on, 13, 2005.

    Google Scholar 

  9. Guoshen Yu, Stephane Mallat, and Emmanuel Bacry. Audio denoising by time-frequency block thresholding. Signal Processing, IEEE Transactions on, 56, 2008.

    Google Scholar 

  10. Yann Salaun. Flexible audio source separation toolbox(faast). http://bass-db.gforge.inria.fr/fasst/ Last accessed on 10-Jan-2016, 2016.

  11. Cadavid Concepts. nuiCapture Analyze. http://nuicapture.com/ Last accessed on 10-Jan-2016, 2016.

  12. Mathworks. Mirtoolbox: An innovative environment for music and audio analysis. http://www.mathworks.in/matlabcentral/fileexchange/24583-mirtoolbox Last accessed on 10-Jan-2016, 2016.

Download references

Acknowledgements

The work of the first author is supported by TCS Research Scholar Program of Tata Consultancy Services of India.

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur, 721302, India

    Tanwi Mallick, Akash Anuj, Partha Pratim Das & Arun Kumar Majumdar

Authors
  1. Tanwi Mallick
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Akash Anuj
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Partha Pratim Das
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Arun Kumar Majumdar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tanwi Mallick .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Balasubramanian Raman

  2. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Sanjeev Kumar

  3. Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Partha Pratim Roy

  4. Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Debashis Sen

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Science+Business Media Singapore

About this paper

Cite this paper

Mallick, T., Anuj, A., Das, P.P., Majumdar, A.K. (2017). Using Musical Beats to Segment Videos of Bharatanatyam Adavus . In: Raman, B., Kumar, S., Roy, P., Sen, D. (eds) Proceedings of International Conference on Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 459. Springer, Singapore. https://doi.org/10.1007/978-981-10-2104-6_52

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-2104-6_52

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2103-9

  • Online ISBN: 978-981-10-2104-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation