Non-photorealistic rendering from multiple images
Author(s): Alberto Bartesaghi, Guillermo Sapiro, Tom Malzbender, Dan Gelb.
Proceedings: IEEE International Conference on Image Processing (ICIP04), pp. 2403--2406, Singapore, October 24-27,
2004.
[BibTeX]
Abstract:
A new paradigm for automatic non-photorealistic rendering
(NPR) is introduced in this paper. Existing NPR approaches
can be categorized in two groups depending on the type of
input they use: image based and object based. Using multiple
images as input to the NPR scheme, we propose a novel
hybrid model that simultaneously uses information from the
image and object domains. The benefit not only comes from
combining the features of each approach, but most important,
it minimizes the need for manual or user assisted tasks
in extracting scene features and geometry, as employed in
virtually all state-of-the-art NPR approaches. We describe
a particular implementation of such an hybrid system and
present a number of automatically generated pen-and-ink
style drawings. This work then shows how to use and extend
well developed techniques in computer vision to address
fundamental problems in image representation and rendering.
Three-dimensional shape rendering from multiple images
Alberto Bartesaghi, Guillermo Sapiro, Tom Malzbender, Dan Gelb.
Graphical Models, Vol. 67, No. 4, pp. 332--346, July,
2005. [BibTeX]