A Phase‐Based Approach for Animating Images Using Video Examples

dc.contributor.authorPrashnani, Ektaen_US
dc.contributor.authorNoorkami, Manelien_US
dc.contributor.authorVaquero, Danielen_US
dc.contributor.authorSen, Pradeepen_US
dc.contributor.editorChen, Min and Zhang, Hao (Richard)en_US
dc.date.accessioned2018-01-10T07:36:30Z
dc.date.available2018-01-10T07:36:30Z
dc.date.issued2017
dc.description.abstractWe present a novel approach for animating static images that contain objects that move in a subtle, stochastic fashion (e.g. rippling water, swaying trees, or flickering candles). To do this, our algorithm leverages example videos of similar objects, supplied by the user. Unlike previous approaches which estimate motion fields in the example video to transfer motion into the image, a process which is brittle and produces artefacts, we propose an Eulerian approach which uses the phase information from the sample video to animate the static image. As is well known, phase variations in a signal relate naturally to the displacement of the signal via the Fourier Shift Theorem. To enable local and spatially varying motion analysis, we analyse phase changes in a complex steerable pyramid of the example video. These phase changes are then transferred to the corresponding spatial sub‐bands of the input image to animate it. We demonstrate that this simple, phase‐based approach for transferring small motion is more effective at animating still images than methods which rely on optical flow.We present a novel approach for animating static images that contain objects that move in a subtle, stochastic fashion (e.g. rippling water, swaying trees, or flickering candles). To do this, our algorithm leverages example videos of similar objects, supplied by the user. Unlike previous approaches which estimate motion fields in the example video to transfer motion into the image, a process which is brittle and produces artefacts, we propose an Eulerian approach which uses the phase information from the sample video to animate the static image. As is well known, phase variations in a signal relate naturally to the displacement of the signal via the Fourier Shift Theorem. To enable local and spatially varying motion analysis, we analyse phase changes in a complex steerable pyramid of the example video.en_US
dc.description.number6
dc.description.sectionheadersArticles
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume36
dc.identifier.doi10.1111/cgf.12940
dc.identifier.issn1467-8659
dc.identifier.pages303-311
dc.identifier.urihttps://doi.org/10.1111/cgf.12940
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf12940
dc.publisher© 2017 The Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectmotion transfer
dc.subjectvideo‐driven image animation
dc.subjectphase‐based motion processing
dc.subjectI.3.7 [Computer Graphics]: Three‐Dimensional Graphics and Realism—Animation
dc.titleA Phase‐Based Approach for Animating Images Using Video Examplesen_US
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