NPAR13
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Item Rasterizing and antialiasing vector line art in the pixel art style(ACM, 2013) Inglis, Tiffany C.; Vogel, Daniel; Kaplan, Craig S.; Forrester Cole and Cindy GrimmPixel artists rasterize vector shapes by hand to minimize artifacts at low resolutions and emphasize the aesthetics of visible pixels. We describe Superpixelator, an algorithm that automates this process by rasterizing vector line art at a low resolution pixel art style. Our technique successfully eliminates most rasterization artifacts and draws smoother curves. To draw shapes more effectively, we use optimization techniques to preserve shape properties such as symmetry, aspect ratio, and sharp angles. Our algorithm also supports ''manual antialiasing, the style of antialiasing used in pixel art. Professional pixel artists report that Superpixelator's results are as good, or better, than hand-rasterized drawings by artists.Item Towards effective evaluation of geometric texture synthesis algorithms(ACM, 2013) AlMeraj, Zainab; Kaplan, Craig S.; Asente, Paul; Forrester Cole and Cindy GrimmIn recent years, an increasing number of example-based Geometric Texture Synthesis (GTS) algorithms have been proposed. However, there have been few attempts to evaluate these algorithms rigorously. We are driven by this lack of validation and the simplicity of the GTS problem to look closer at perceptual similarity between geometric arrangements. Using samples from a geological database, our research first establishes a dataset of geometric arrangements gathered from multiple synthesis sources. We then employ the dataset in two evaluation studies. Collectively these empirical methods provide formal foundations for perceptual studies in GTS, insight into the robustness of GTS algorithms and a better understanding of similarity in the context of geometric texture arrangements.