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&rsquo / s key characteristics in
his drawing.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12614899/index.pdf |
| Date | 01 September 2012 |
| Creators | Kuruoglu, Betul |
| Contributors | Yarman Vural, Fatos Tunay |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | Access forbidden for 1 year |
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