State of the Art: A Taxonomy of Artistic Stylization Techniques for Images and Video
Kyprianidis, JE, Collomosse, JP, Isenberg, T and Wang, T (2012) State of the Art: A Taxonomy of Artistic Stylization Techniques for Images and Video IEEE Transactions on Visualization and Computer Graphics, volume. ISSN 1077-2626
Available under License : See the attached licence file.
This paper surveys the field of non-photorealistic rendering (NPR), focusing on techniques for transforming 2D input (images and video) into artistically stylized renderings. We first present a taxonomy of the 2D NPR algorithms developed over the past two decades, structured according to the design characteristics and behavior of each technique. We then describe a chronology of development from the semi-automatic paint systems of the early nineties, through to the automated painterly rendering systems of the late nineties driven by image gradient analysis. Two complementary trends in the NPR literature are then addressed, with reference to our taxonomy. First, the fusion of higher level computer vision and NPR, illustrating the trends toward scene analysis to drive artistic abstraction and diversity of style. Second, the evolution of local processing approaches toward edge-aware filtering for real-time stylization of images and video. The survey then concludes with a discussion of open challenges for 2D NPR identified in recent NPR symposia, including topics such as user and aesthetic evaluation.
Copyright 2012 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
|Divisions:||Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing|
|Depositing User:||Symplectic Elements|
|Date Deposited:||23 Oct 2012 09:00|
|Last Modified:||12 Oct 2014 01:33|
Actions (login required)
Downloads per month over past year