ToonCap: A Layered Deformable Model for Capturing Poses From Cartoon Characters

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dc.contributor.authorFan, Xinyien_US
dc.contributor.authorBermano, Amit H.en_US
dc.contributor.authorKim, Vladimir G.en_US
dc.contributor.authorPopović, Jovanen_US
dc.contributor.authorRusinkiewicz, Szymonen_US
dc.contributor.editorAydın, Tunç and Sýkora, Danielen_US
dc.date.accessioned2018-11-10T20:57:22Z
dc.date.available2018-11-10T20:57:22Z
dc.date.issued2018
dc.description.abstractCharacters in traditional artwork such as children's books or cartoon animations are typically drawn once, in fixed poses, with little opportunity to change the characters' appearance or re-use them in a different animation. To enable these applications one can fit a consistent parametric deformable model - a puppet - to different images of a character, thus establishing consistent segmentation, dense semantic correspondence, and deformation parameters across poses. In this work we argue that a layered deformable puppet is a natural representation for hand-drawn characters, providing an effective way to deal with the articulation, expressive deformation, and occlusion that are common to this style of artwork. Our main contribution is an automatic pipeline for fitting these models to unlabeled images depicting the same character in various poses. We demonstrate that the output of our pipeline can be used directly for editing and re-targeting animations.en_US
dc.description.sectionheadersCartoons and Beyond
dc.description.seriesinformationExpressive: Computational Aesthetics, Sketch-Based Interfaces and Modeling, Non-Photorealistic Animation and Rendering
dc.identifier.doi10.1145/3229147.3229149
dc.identifier.isbn978-1-4503-5892-7
dc.identifier.issn2079-8679
dc.identifier.urihttps://doi.org/10.1145/3229147.3229149
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1145/3229147-3229149
dc.publisherACMen_US
dc.titleToonCap: A Layered Deformable Model for Capturing Poses From Cartoon Charactersen_US
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