Stylized Depiction of Images with Normals

Abstract:

This paper investigates the creation of non-photorealistic illustrations
from a type of data lying between simple 2D images and full 3D models:
images with both a color (albedo) and a surface normal stored at each
pixel. Images with normals combine an acquisition process only mildly
more complex than that for digital photographs (and significantly easier
than 3D scanning) with the power and flexibility of tools similar to
those originally developed for full 3D models. We investigate methods
for signal processing on images with normals, developing algorithms for
scale-space analysis, derivative (i.e., curvature) estimation, and
segmentation. These are used to implement analogues of stylized
rendering techniques such as toon shading, line drawing, curvature
shading, and exaggerated shading. We show that our rendering pipeline
can produce detailed yet understandable illustrations in medical,
technical, and archaeological domains.