As-Rigid-As-Possible Image Registration for Hand-drawn Cartoon Animations
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We present a new approach to deformable image registration suitable for articulated images such as hand-drawn cartoon characters and human postures. For such type of data state-of-the-art techniques typically yield undesirable results. We propose a novel geometrically motivated iterative scheme where point movements are decoupled from shape consistency. By combining locally optimal block matching with as-rigid-as-possible shape regularization, our algorithm allows us to register images undergoing large free-form deformations and appearance variations. We demonstrate its practical usability in various challenging tasks performed in the cartoon animation production pipeline including unsupervised inbetweening, example-based shape deformation, auto-painting, editing, and motion retargeting.
Proceedings of the 7th International Symposium on Non-Photorealistic Animation and Rendering, pp. 25–33, 2009 Example-Based Shape Deformation:
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