Facial Expression Synthesis using a Global-Local Multilinear Framework

dc.contributor.authorWang, Mengjiaoen_US
dc.contributor.authorBradley, Dereken_US
dc.contributor.authorZafeiriou, Stefanosen_US
dc.contributor.authorBeeler, Thaboen_US
dc.contributor.editorPanozzo, Daniele and Assarsson, Ulfen_US
dc.date.accessioned2020-05-24T12:51:36Z
dc.date.available2020-05-24T12:51:36Z
dc.date.issued2020
dc.description.abstractWe present a practical method to synthesize plausible 3D facial expressions for a particular target subject. The ability to synthesize an entire facial rig from a single neutral expression has a large range of applications both in computer graphics and computer vision, ranging from the efficient and cost-effective creation of CG characters to scalable data generation for machine learning purposes. Unlike previous methods based on multilinear models, the proposed approach is capable to extrapolate well outside the sample pool, which allows it to plausibly predict the identity of the target subject and create artifact free expression shapes while requiring only a small input dataset. We introduce global-local multilinear models that leverage the strengths of expression-specific and identity-specific local models combined with coarse motion estimations from a global model. Experimental results show that we achieve high-quality, plausible facial expression synthesis results for an individual that outperform existing methods both quantitatively and qualitatively.en_US
dc.description.number2
dc.description.sectionheadersFaces
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume39
dc.identifier.doi10.1111/cgf.13926
dc.identifier.issn1467-8659
dc.identifier.pages235-245
dc.identifier.urihttps://doi.org/10.1111/cgf.13926
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13926
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectComputing methodologies
dc.subjectComputer vision representations
dc.subjectShape modeling
dc.titleFacial Expression Synthesis using a Global-Local Multilinear Frameworken_US
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