Facial caricature generation using a quadratic deformation model

Authors:
M. Obaid;D. Lond;R. Mukundan;M. Billinghurst
Affiliations:
University of Canterbury, Christchurch, New Zealand and University of Canterbury, New Zealand;University of Canterbury, New Zealand;University of Canterbury, New Zealand;University of Canterbury, Christchurch, New Zealand
Venue:
Proceedings of the International Conference on Advances in Computer Enterntainment Technology
Year:
2009

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Abstract

In this paper we propose a novel approach for generating expressive caricatures from an input image. The novelty of this work comes from combining an Active Appearance Model facial feature extraction system with a quadratic deformation model representation of facial expressions. The extracted features are deformed using the quadratic deformation parameters, resulting in an expressive caricature. The facial feature extraction requires an offline training process which uses natural expression annotated images from 30 model subjects, selected randomly from the Cohn-Kanade Database. The results show that from an input facial image, expressive caricatures are generated for the main six face expressions (smile, sad, fear, surprise, disgust, and anger). The proposed approach yields to promising expressive caricatures, and could lead to future research directions in the field of non-photorealistic rendering. In addition, the proposed approach can be employed in entertaining standalone applications or caricature animations.