Abstract:

We present an example-based system for translating line drawings into different styles. The system is given a training set of many different lines, each drawn by an artist in various styles, which is used to translate new lines made by a user into a particular desired style with a {it K-nearest neighbor} algorithm. This algorithm fits each input line as a linear combination of the several training lines in the same style which are most similar to it. The fit line can then be rendered in different styles because the training set contains versions of each training line in each style. Our example-based approach has a number of advantages over conventional parameteric approaches to translating style. It can handle styles which are difficult to describe parametrically, and its repertoire can be easily extended by the user at any time. Moreover, given appropriate representations, it can be generalized to modify the style of other kinds of graphics objects, such as the font of a letter or the movement style of an animated character.