Example based caricature synthesis.

Abstract

The likeness of a synthesized caricature and the original face image is an essential and often overlooked part of caricature production. In this paper, we present an example based caricature synthesis technique, consisting of shape exaggeration, relationship exaggeration, and optimization for likeness. Rather than relying on a large training set of caricature face pairs, our shape exaggeration step is based on only one or a small number of examples of facial elements (e.g., eyes and nose). The relationship exaggeration step introduces two definitions which facilitate global facial feature synthesis. The first is the T-shape rule, which describes the relative relationship between the facial elements in an intuitive manner. The second is the so-called proportions, which characterizes the facial features in a proportion form. Finally, we introduce a similarity metric as the likeness metric based on the Modified Hausdorff Distance (MHD) which allows us to optimize the configuration of facial elements, maximizing the likeness while satisfying a number of constraints. The effectiveness of our algorithm is demonstrated with experimental results.