A second look at non-photorealistic rendering

Non-photorealistic rendering(NPR) is a thread of research I've been following for a while, without ever being completely satisfied with publications in the field. NPR is often overlooked by computer graphics researchers as  it is difficult to evaluate the quality of the work numerically. The combination of perception methods with NPR can address this issue, at least for some applications (It is certainly the case for visualization applications). Perception theories are verified using psychophysics experiments which consist in showing images to a group of subjects, asking them questions about those images and computing some statistics on their answers.

NPR hasn't drawn any attention from the artistic crowd either because the results shown in scientific publications often lack aesthetic qualities.

This issue is partly addressed by the newly proposed programming paradigms I discussed in a previous post. I'm confident that programming these effects will be accessible to even the most novice programmers and most probably to the crowd of artists who can already script in Maya or AfterEffects. If it is the case, we might start to see some interesting NPR-generate images.

Another problem is that traditional 3D modelling tools only bring indirect control to animators over the final look of their images. The 2.5D cartoon-type of approach I discussed in a previous post might help giving more direct control.

One other problem I find is that every object in a scene has to be physically coherent in 3D, which is a serious limitation for 2D artists. A paper called "Modeling and Rendering impossible figures" presented an approach that might be the beginning of a solution to that problem. Here's a simple video explaining the approach:



Finally, the most important problem for me is that you can always tell NPR images have been generated from a 3D model. Rendered objects usually look like 3D models on which paint or hatching patterns have been applied rather than true 2D depictions. Some publications are starting to address this issue this year by using a combination of 3D and 2D information in the rendering process. It was the case for the 2.5D cartoon paper I discussed earlier and it is the case again in a talk I attended thursday morning called "NPR Gabor Noise for Coherent Stylization".

When it comes to animation as an art form, my preferred technique is still frame-by-frame 2D animation. But what I've seen this year at Siggraph forces me to take a second look at NPR, especially since I think it could be very useful for my visualization work.

The conference is now over. This post is being edited early friday morning on a boarding dock in the Pearson airport. I'll write a last post later on this weekend about my predictions for future trends in graphics. I think it will be funny to read that in 10 years from now.