Automatic cartoon generation by learning the style of an artist

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2012
Kuruoğlu, Betül
In this study, we suggest an algorithm for generating cartoons from face images automatically. The suggested method learns drawing style of an artist and applies this style to the face images in a database to create cartoons. The training data consists of a set of face images and corresponding cartoons, drawn by the same artist. Initially, a set of control points are labeled and indexed to characterize the face in the training data set for both images and corresponding caricatures. Then, their features are extracted to model the style of the artist. Finally, a similarity matrix of real face image set and the input image are constructed. With the help of the similarity matrix, Distance-Weighted Nearest Neighbor algorithm calculates the exaggeration coefficients which caricaturist would have designed for the input image in his mind. In caricature generation phase, Moving Least Squares algorithm is applied to distort the input image based on these coefficients. Caricatures generated by this approach successfully cover most of the caricaturist’s key characteristics in his drawing.

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Citation Formats
B. Kuruoğlu, “Automatic cartoon generation by learning the style of an artist,” M.S. - Master of Science, Middle East Technical University, 2012.