Paint By Relaxation

Aaron Hertzmann

Media Research Laboratory
Department of Computer Science
Courant Institute of Mathematical Sciences
New York University


We use relaxation to produce painted imagery from images and video. An energy function is first specified; we then search for a painting with minimal energy. The appeal of this strategy is that, ideally, we need only specify what we want, not how to directly compute it. Because the energy function is very difficult to optimize, we use a relaxation algorithm combined with search heuristics.

This formulation allows us to specify painting style by varying the relative weights of energy terms. The basic energy function yields an economical style that conveys an image with few strokes. This style produces greater temporal coherence for video than previous techniques. The system allows as fine user control as desired: the user may interactively change the painting style, specify variations of style over an image, and/or add specific strokes to the painting.

CGI 2001 paper:

NYU CS Tech Report 2000-801 (more detailed than paper version):
PDF (18MB)
Compressed PostScript (15MB)

Project Page: Painterly rendering

Project Page: Non-photorealistic rendering

Copyright © 2000 Aaron Hertzmann