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Hair Interpolation for Portrait Morphing

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Abstract

In this paper we study the problem of hair interpolation: given two 3D hair models, we want to generate a sequence of intermediate hair models that transform from one input to another both smoothly and aesthetically pleasing. We propose an automatic method that efficiently calculates a many-to-many strand correspondence between two or more given hair models, taking into account the multi-scale clustering structure of hair. Experiments demonstrate that hair interpolation can be used for producing more vivid portrait morphing effects and enabling a novel example-based hair styling methodology, where a user can interactively create new hairstyles by continuously exploring a “style space” spanning multiple input hair models.

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