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St Jeschke:
"Rendering Diffusion Curves in 2 and 3 Dimensions";
Talk: Max-Planck-Institut für Informatik, MPII Saarbruecken, Deutschland (invited); 2010-10-07 - 2010-10-08.

Diffusion curve images (DCI) provide a powerful tool for efficient 2D image generation, storage and manipulation. A DCI consist of curves with colors defined on either side. By diffusing these colors over the image, the final result includes sharp boundaries along the curves with smoothly shaded regions between them. The first part of the talk presents a new Laplacian surface solver for a stable rendering of DCIs. It consists of a robust rasterization technique to transform the algebraic curves to the discrete image domain, and a variable stencil size diffusion solver that solves the minimal surface problem. The solver is proven to converge to the right solution, it is at least as fast as commonly used multigrid solvers, but much simpler to implement, works for arbitrary image resolutions, as well as 8 bit data. The second part of the talk extends the application of diffusion curves to render high quality surface details on 3D objects. The first extension is a view dependent warping technique that dynamically allocates more texture memory for details close to the observer. The second extension is a dynamic feature embedding technique that retains crisp, anti-aliased curve details even in extreme closeups. The third extension is the application of dynamic feature embedding to displacement mapping and geometry images. Our results show high quality renderings at interactive frame rates.

Diffusion curves