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Depth-Aware Motion Magnification

  • Julian F. P. KooijEmail author
  • Jan C. van Gemert
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9912)

Abstract

This paper adds depth to motion magnification. With the rise of cheap RGB+D cameras depth information is readily available. We make use of depth to make motion magnification robust to occlusion and large motions. Current approaches require a manual drawn pixel mask over all frames in the area of interest which is cumbersome and error-prone. By including depth, we avoid manual annotation and magnify motions at similar depth levels while ignoring occlusions at distant depth pixels. To achieve this, we propose an extension to the bilateral filter for non-Gaussian filters which allows us to treat pixels at very different depth layers as missing values. As our experiments will show, these missing values should be ignored, and not inferred with inpainting. We show results for a medical application (tremors) where we improve current baselines for motion magnification and motion measurements.

Keywords

Motion magnification Bilateral filter RGB+D 

Notes

Acknowledgments

This work is part of the research programme Technology in Motion (TIM [628.004.001]), financed by the Netherlands Organisation for Scientific Research (NWO).

Supplementary material

Supplementary material 1 (mp4 40116 KB)

Supplementary material 2 (mp4 46260 KB)

419983_1_En_28_MOESM3_ESM.pdf (1.9 mb)
Supplementary material 3 (pdf 1925 KB)

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Delft University of TechnologyDelftThe Netherlands
  2. 2.Leiden University Medical CenterLeidenThe Netherlands

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