Skip to main content
SpringerLink
Log in

Efficient Motion Magnification

  • Conference paper
Intelligent Information and Database Systems (ACIIDS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9622))

Included in the following conference series:

  • 1581 Accesses

Abstract

Video motion magnification (VMM) allows to amplify hardly visible changes in the video input sequence. It is possible to amplify breathing motion of hospital patients or oscillations of some mechanical element without need to connect measuring devices. On the other hand modified VMM algorithm can be used to extinguish motion before processing with another method. Unfortunately, algorithm in its full, but slowest version uses new pyramids instead laplacian ones and requires remarkable computational power in each stage of processing and that problem is solved by GPU-based implementation of basic operations using CUDA technology and scheduling them by CPU. That approach lets to run all computations on GPU. Additionally in comparison with previous studies temporal filter was changed to butterworth one. Although testing hardware was only able to run low resolution in real time, there are no doubts that better GPU would be able to run 640 × 480 resolution in real time.

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

Access this chapter

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Institutional subscriptions

References

  1. Wadhwa, N., Rubinstein, M., Durand, F., Freeman, W.T.: Riesz pyramids for fast phase-based video magnification. In: IEEE International Conference on Computational Photography (ICCP) (2014)

    Google Scholar 

  2. Wadhwa, N., Rubinstein, M., Durand, F., Freeman, W.T.: Phase-based video motion processing. ACM Trans. Graph. 32(4), 80:1–80:10 (2013)

    Article  MATH  Google Scholar 

  3. Wu, H.-Y., Rubinstein, M., Shih, E., Guttag, J., Durand, F., Freeman, W.: Eulerian video magnification for revealing subtle changes in the world. ACM Trans. Graph. 31(4), 65:1–65:8 (2012)

    Article  Google Scholar 

  4. Lim, J.S.: Two-Dimensional Signal and Image Processing. Prentice Hall, Inc., Englewood Cliffs (1990)

    Google Scholar 

  5. Ryt, A., Sobel, D., Kwiatkowski, J., Domzal, M., Jedrasiak, K., Nawrat, A.: Real-time laser point tracking. In: Chmielewski, L.J., Kozera, R., Shin, B.-S., Wojciechowski, K. (eds.) ICCVG 2014. LNCS, vol. 8671, pp. 542–551. Springer, Heidelberg (2014). ISBN (Print) 978-3-319-11330-2, ISBN (Online) 978-3-319-11331-9

    Google Scholar 

  6. Nawrat, A., Jedrasiak, K.: SETh System Spation-Temporal Object Tracking Using Combined Color And Motion Features, Electrical And Computer Engineering Series, pp. 67–72 (2009)

    Google Scholar 

  7. Internet source, accessed August 2015. http://people.csail.mit.edu/nwadhwa/riesz-pyramid/videos/Drum.mp4

  8. Internet source. http://docs.nvidia.com/cuda/. Accessed June 2015

  9. Internet source. http://opencv.org/. Accessed June 2015

  10. Internet source. https://github.com/ruohoruotsi/Butterworth-Filter-Design. Accessed August 2015

Download references

Acknowledgement

This work has been supported by National Centre for Research and Development as a project ID: DOB-BIO6/11/90/2014, Virtual Simulator of Protective Measures of Government Protection Bureau.

Author information

Authors and Affiliations

  1. Institute of Automation, Silesian University of Technology, Gliwice, Poland

    Mariusz Domżał, Dawid Sobel, Jan Kwiatkowski, Karol Jędrasiak & Aleksander Nawrat

Authors
  1. Mariusz Domżał
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dawid Sobel
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jan Kwiatkowski
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Karol Jędrasiak
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Aleksander Nawrat
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Karol Jędrasiak .

Editor information

Editors and Affiliations

  1. Wrocław University of Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Wrocław University of Technology, Wrocław, Poland

    Bogdan Trawiński

  3. Iwate Prefectural University, Takizawa, Japan

    Hamido Fujita

  4. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Domżał, M., Sobel, D., Kwiatkowski, J., Jędrasiak, K., Nawrat, A. (2016). Efficient Motion Magnification. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9622. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49390-8_47

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-49390-8_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49389-2

  • Online ISBN: 978-3-662-49390-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation