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Saliency Driven Video Motion Magnification

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Computer Vision, Pattern Recognition, Image Processing, and Graphics (NCVPRIPG 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 841))

Abstract

The main goal of the proposed work is to detect certain spatial and temporal changes in videos that are not visible to the human eye and magnify them in order to make them perceptible while making sure that the background noise is not amplified. We apply Eulerian motion magnification on only the salient area of each frame of the video. The salient object is processed independent of the rest of the image using alpha matting aided by scribbles. We demonstrate the need to isolate the salient object from background motions and propose a simple and efficient way to do so. The proposed algorithm is tested on videos with imperceptible motion along with background motion to illustrate the significance of the proposed method. We compare the proposed method with linear and phase based Eulerian motion magnification techniques.

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Acknowledgement

The authors would like to thank SERB-DST for support through Young Scientists Startup Research Grant.

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Authors and Affiliations

  1. Electrical Engineering, IIT Gandhinagar, Gandhinagar, Gujarat, India

    Manisha Verma & Shanmuganathan Raman

  2. Computer Science Engineering, PES University, Bengaluru, Karnataka, India

    Ramyani Ghosh

Authors
  1. Manisha Verma
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  2. Ramyani Ghosh
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  3. Shanmuganathan Raman
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Corresponding author

Correspondence to Manisha Verma .

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Editors and Affiliations

  1. Indian Institute of Technology Mandi, Mandi, Himachal Pradesh, India

    Renu Rameshan

  2. Indraprastha Institute of Information Technology, New Delhi, India

    Chetan Arora

  3. Indian Institute of Technology, New Delhi, India

    Sumantra Dutta Roy

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Verma, M., Ghosh, R., Raman, S. (2018). Saliency Driven Video Motion Magnification. In: Rameshan, R., Arora, C., Dutta Roy, S. (eds) Computer Vision, Pattern Recognition, Image Processing, and Graphics. NCVPRIPG 2017. Communications in Computer and Information Science, vol 841. Springer, Singapore. https://doi.org/10.1007/978-981-13-0020-2_9

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  • DOI: https://doi.org/10.1007/978-981-13-0020-2_9

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-0019-6

  • Online ISBN: 978-981-13-0020-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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