Painterly rendering with vector field based feature extraction

Authors:
Chen Pang;Mingli Song;Jiajun Bu;Chun Chen;Dong Wang
Affiliations:
Zhejiang University – Microsoft Joint Lab of Visual Perception, Key Lab of Ministry of Education, Zhejiang University, Hangzhou, P.R. China;Zhejiang University – Microsoft Joint Lab of Visual Perception, Key Lab of Ministry of Education, Zhejiang University, Hangzhou, P.R. China;Zhejiang University – Microsoft Joint Lab of Visual Perception, Key Lab of Ministry of Education, Zhejiang University, Hangzhou, P.R. China;Zhejiang University – Microsoft Joint Lab of Visual Perception, Key Lab of Ministry of Education, Zhejiang University, Hangzhou, P.R. China;Zhejiang University – Microsoft Joint Lab of Visual Perception, Key Lab of Ministry of Education, Zhejiang University, Hangzhou, P.R. China
Venue:
ICAT'06 Proceedings of the 16th international conference on Advances in Artificial Reality and Tele-Existence
Year:
2006

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Abstract

In this paper, a novel technique is presented to incorporate vector field based feature extraction schemes into painterly rendering. This approach takes a raster photograph as input and automatically creates a hand-painting style picture. Via techniques formerly used in image segmentation, a vector field representation are generated, identifying color and texture variations at each pixel location, and a series of brush strokes are created with sizes and alignments controlled by the vector field and color matched from the original picture. Moreover, different scale parameters could be utilized to produce several vector fields depicting images features of the original photograph from rough outline to detail. The final output could be rendered first by brushstrokes in the coarsest scale and refined progressively. Unlike conventional techniques that used taking account only of local color gradients, this approach employs multi-scale feature extraction scheme to guide stroke generation with image structure on larger scale.