Non-photorealistic rendering from multiple images

Alberto Bartesaghi, Guillermo Sapiro, Tom Malzbender, Dan Gelb

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)2403-2406
Number of pages4
JournalProceedings - International Conference on Image Processing, ICIP
Volume4
DOIs
StatePublished - 2004
Externally publishedYes
Event2004 International Conference on Image Processing, ICIP 2004 - , Singapore
Duration: Oct 18 2004Oct 21 2004

All Science Journal Classification (ASJC) codes

  • General Engineering

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