Depth-aware motion magnification

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

28 Citations (Scopus)


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.
Original languageEnglish
Title of host publicationProceedings 14th European Conference on Computer Vision - ECCV 2016
EditorsB. Leibe, J. Matas, N. Sebe, M. Welling
Place of PublicationCham, Switzerland
ISBN (Electronic)978-3-319-46454-1
ISBN (Print)978-3-319-46453-4
Publication statusPublished - 2016
EventECCV 2016: 29th European Conference on Computer Vision - Amsterdam, Netherlands
Duration: 8 Oct 201616 Oct 2016

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743


ConferenceECCV 2016


  • Motion magnification
  • Bilateral filter
  • RGB+D


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