Fast Shape-Simplifying Image Abstraction Using Graphics Hardware

Authors:
Hanli Zhao;Xiaogang Jin;Jianbing Shen;Li Shen;Ruifang Pan
Affiliations:
State Key Lab of CAD & CG, Zhejiang University, China;State Key Lab of CAD & CG, Zhejiang University, China;School of Computer & Technology, Beijing Institute of Technology, China;State Key Lab of CAD & CG, Zhejiang University, China;Zhejiang University of Media and Communications, China
Venue:
Edutainment '09 Proceedings of the 4th International Conference on E-Learning and Games: Learning by Playing. Game-based Education System Design and Development
Year:
2009

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Abstract

This paper presents a new GPU-based method for creating abstracted representations of photographs. Based on the constrained mean curvature flow and the Shock filter, our approach simplifies both shapes and colors simultaneously while preserving and conveying the directionality of important features and shape boundaries. The level of abstraction can be intuitively controlled by iteratively and incrementally applying the algorithm. Note that the whole pipeline design is highly parallel, enabling a GPU-based implementation. Our GPU-based method outperforms the CPU-based one with two magnitudes of speedup. Several experimental examples are shown to demonstrate both the effectiveness and efficiency of the proposed method.