Generating target-character-animation sequences based on style-aware puppets patterned after source-character-animation sequences

US10789754B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-10789754-B2
Application numberUS-201816047839-A
CountryUS
Kind codeB2
Filing dateJul 27, 2018
Priority dateJul 27, 2018
Publication dateSep 29, 2020
Grant dateSep 29, 2020

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  5. First independent claim

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Abstract

Official abstract text for this publication.

This disclosure relates to methods, non-transitory computer readable media, and systems that use style-aware puppets patterned after a source-character-animation sequence to generate a target-character-animation sequence. In particular, the disclosed systems can generate style-aware puppets based on an animation character drawn or otherwise created (e.g., by an artist) for the source-character-animation sequence. The style-aware puppets can include, for instance, a character-deformational model, a skeletal-difference map, and a visual-texture representation of an animation character from a source-character-animation sequence. By using style-aware puppets, the disclosed systems can both preserve and transfer a detailed visual appearance and stylized motion of an animation character from a source-character-animation sequence to a target-character-animation sequence.

First claim

Opening claim text (preview).

We claim: 1. A system comprising: at least one processor; and at least one non-transitory computer memory comprising a source-character-animation sequence of a two-dimensional animation character portrayed in source drawings corresponding to a source-skeletal-animation sequence of a source skeleton in source-skeletal poses, and instructions that, when executed by at least one processor, cause the system to: generate style-aware puppets for the source drawings portraying the two-dimensional animation character, each style-aware puppet comprising a coarse-deformation model of a source drawing portraying the two-dimensional animation character from the source-character-animation sequence, a residual-deformation model of the source drawing portraying the two-dimensional animation character, a skeletal-difference map comprising differences between a source-skeletal pose and a stylized-skeletal pose corresponding to the source drawing portraying the two-dimensional animation character, and a visual-texture representation of the source drawing portraying the two-dimensional animation character; identify a target-skeletal-animation sequence comprising a target skeleton in target-skeletal poses; generate target-style-aware puppets corresponding to the target-skeletal-animation sequence by, for a target-skeletal pose of the target-skeletal poses: comparing the target-skeletal pose with the source-skeletal-animation sequence to select a set of source-skeletal poses; identifying a set of source drawings from the source-character-animation sequence from the source-character-animation sequence corresponding to the set of source-skeletal poses; blending the style-aware puppets corresponding to the set of source drawings to create a target-style-aware puppet; and based on the target-style-aware puppets, generate a target-character-animation sequence of the two-dimensional animation character portrayed in target drawings corresponding to the target-skeletal-animation sequence. 2. The system of claim 1 , further comprising instructions that, when executed by the at least one processor, cause the system to: compare the target-skeletal pose with the source-skeletal-animation sequence to select the set of source-skeletal poses by: identifying a set of target-skeletal poses adjacent to the target-skeletal pose in the target-skeletal-animation sequence; and selecting the set of source-skeletal poses by comparing trajectories of joints across the set of target-skeletal poses with trajectories of joints across the set of source-skeletal poses; and identify the set of source drawings by identifying source drawings corresponding to the set of source-skeletal poses in the source-character-animation sequence. 3. The system of claim 1 , further comprising instructions that, when executed by the at least one processor, cause the system to blend the style-aware puppets corresponding to the set of source drawings by: interpolating coarse-deformation models for the style-aware puppets corresponding to the set of source drawings to create a modified-coarse-deformation model for the target-style-aware puppet; linearly blending residual-deformation models for the style-aware puppets corresponding to the set of source drawings to create a modified-residual-deformation model for the target-style-aware puppet; linearly blending skeletal-difference maps for the style-aware puppets to create a modified-skeletal-difference map for the target-style-aware puppet; and linearly blending visual-texture representations for the style-aware puppets corresponding to the set of source drawings to create a modified-visual-texture representation for the target-style-aware puppet. 4. The system of claim 3 , further comprising instructions that, when executed by the at least one processor, cause the system to linearly blend the visual-texture representations for the style-aware puppets corresponding to the set of source drawings by: rectifying the visual-texture representations for each style-aware puppet corresponding to the set of source drawings based on the coarse-deformation model for the style-aware puppet and the residual-deformation model for the style-aware puppet; and linearly blending the rectified visual-texture representations to create the modified-visual-texture representation for the target-style-aware puppet. 5. The system of claim 4 , further comprising instructions that, when executed by the at least one processor, cause the system to, based on the target-style-aware puppet, generate the target-character-animation sequence of the two-dimensional animation character portrayed in the target drawings by, for the target-style-aware puppet: applying the modified-skeletal-difference map to the target-skeletal pose to generate a stylized-target-skeletal pose; and utilizing the modified-coarse-deformation model for the target-style-aware puppet, the modified-residual-deformation model for the target-style-aware puppet, and the stylized-target-skeletal pose to generate a target drawing portraying the two-dimensional animation character. 6. The system of claim 4 , further comprising instructions that, when executed by the at least one processor, cause the system to, based on the target-style-aware puppet, generate the target-character-animation sequence of the two-dimensional animation character portrayed in the target drawings by, for the target-style-aware puppet, utilize a segmentation-guidance channel and a temporal-appearance-guidance channel with the modified-visual-texture representation to generate the two-dimensional animation character in the target drawing. 7. The system of claim 1 , further comprising instructions that, when executed by the at least one processor, cause the system to determine the coarse-deformation model of the source drawing portraying the two-dimensional animation character by: generating a layered as-rigid-as-possible (“ARAP”) mesh for a layered-template puppet, wherein the layered ARAP mesh comprises ARAP mesh layers corresponding to semantic layers of the layered-template puppet; and adjusting the ARAP mesh layers of the layered ARAP mesh to conform to the semantic layers of the layered-template puppet positioned according to the source drawing. 8. The system of claim 1 , further comprising instructions that, when executed by the at least one processor, cause the system to select the set of source drawings from the source-character-animation sequence by: identifying a set of target-skeletal poses adjacent to the target-skeletal pose in the target-skeletal-animation sequence comprising the target skeleton in the target-skeletal poses; selecting a set of source-skeletal poses analogous to the set of target-skeletal poses by comparing trajectories of joints across the set of target-skeletal poses with trajectories of joints across the set of source-skeletal poses; and selecting the set of source drawings by identifying source drawings corresponding to the set of source-skeletal poses in the source-character-animation sequence. 9. The system of claim 8 , further comprising instructions that, when executed by the at least one processor, cause the system to blend the style-aware puppets corresponding to the set of source drawings to create the target-style-aware puppet by: identifying additional sets of source drawings from the source-character-animation sequence, the additional sets of source drawings each comprising at least one source drawing overlapping with the set of source drawings in the source-character-animation sequence; and blending style-aware puppets corresponding to the additional sets of source drawings with the style-aware puppets corresponding to the set of source drawings. 10. The syst

Assignees

Inventors

Classifications

  • G06T13/80Primary

    Two-dimensional [2D] animation, e.g. using sprites · CPC title

  • G06T13/40Primary

    of characters, e.g. humans, animals or virtual beings · CPC title

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What does patent US10789754B2 cover?
This disclosure relates to methods, non-transitory computer readable media, and systems that use style-aware puppets patterned after a source-character-animation sequence to generate a target-character-animation sequence. In particular, the disclosed systems can generate style-aware puppets based on an animation character drawn or otherwise created (e.g., by an artist) for the source-character-…
Who is the assignee on this patent?
Adobe Inc, Czech Technical Univ In Prague
What technology area does this patent fall under?
Primary CPC classification G06T13/80. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Sep 29 2020 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).