Generating Nonperspective Images Using Automatic Viewpoint Selection

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  • MASHIO Kairi
    Graduate School of Frontier Sciences, The University of Tokyo
  • YOSHIDA Kenichi
    Graduate School of Frontier Sciences, The University of Tokyo
  • TAKAHASHI Shigeo
    Graduate School of Frontier Sciences, The University of Tokyo
  • OKADA Masato
    Graduate School of Frontier Sciences, The University of Tokyo RIKEN Brain Science Institute

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  • 最適視点計算を用いた非透視投影図の自動生成
  • サイテキ シテン ケイサン オ モチイタ ヒトウシ トウエイズ ノ ジドウ セイセイ

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Abstract

Hand-drawn pictures differ from ordinary perspective images in that the entire scene is composed of local feature regions each of which is projected as seen from its own vista point. This type of projection, called nonperspective projection, has served as one of the common media for our visual communication while its automatic generation process still needs more research. This paper presents a method for automatically generating aesthetic nonperspective images by simulating the deformation principles seen in such hand-drawn pictures. The proposed method first locates the optimal viewpoint for each feature region by maximizing the associated viewpoint entropy value. These optimal viewpoints are then incorporated into the 3D camera parameter field, which is represented by 3D grid samples of camera parameters. Finally, the camera parameter field is smoothed out in order to eliminate any unexpected discontinuities between neighboring feature regions, by taking advantage of image restoration techniques. Several nonperspective images are generated to demonstrate the applicability of the proposed method.

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