Sample-Based Painterly Image Generation Using GIST

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  • Abe Noriyuki
    Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi
  • Toyoura Masahiro
    Interdisciplinary Research Institution of Medicine and Engineering, University of Yamanashi
  • Mao Xiaoyang
    Interdisciplinary Research Institution of Medicine and Engineering, University of Yamanashi

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Other Title
  • 大局的特徴量GIST を用いた作品例に基づく絵画調画像生成
  • タイキョクテキ トクチョウリョウ GIST オ モチイタ サクヒンレイ ニ モトズク カイガチョウガゾウ セイセイ

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Description

We present a new technique for artistic style transferring by considering the perceptual structure matching between source image and target images. Given a photograph, our technique first searches for an existing art work on a similar scene through using the computational model of GIST perception and then transfers both the color and brush texture from it by considering the structure matching between two images. The proposed method is fully automatic and can be used for transferring any styles. Subject studies have been conducted to validate the effectiveness of our newly designed GIST feature vector as well as the enhanced color and texture transferring considering structure matching.

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