Colored exaggerative caricature creation using inter- and intra-correlations of feature shapes and positions

This paper develops a system comprising a statistics-based exaggerative (SBE) module and a non-photorealistic rendering (NPR) module for the automatic creation of colored facial caricatures with exaggerated facial features and individual facial details such as beards and moles. Unlike previous research that focused on the inter-correlation (the difference between the facial features of input image and those of the mean face in the training database), the SBE module exaggerates the input image utilizing an iterative approach based on both inter- and intra-correlations of the facial features. The intra-correlation considered in this study makes the comparison with other features within the same input image, and has the effect of exaggerating the major facial features while simultaneously subduing the visual impact of non-major facial features. The NPR module consists of a black-and-white sketch creation process and a colored facial cartoon creation process. The results of the two processes are combined to generate a colored cartoon-like sketch, which is then warped into a colored exaggerative facial caricature based on the corresponding exaggerative shape and position created by the SBE module. The experimental results demonstrate that the proposed method can emphasize the major characteristics of a face better than previous methods that only considered feature inter-correlation.

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► SBE module generates an exaggerated shape of facial image.
► NPR module generates a colored cartoon-like sketch.
► The results of SBE and NPR module are integrated to create colored caricatures.
► SBE module considers both inter- and intra-correlations of the facial features.
► The scaling factors of facial features are determined in an adaptive way.