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A DoF-Based Efficient Image Abstraction

피사계 심도를 고려한 효율적인 이미지 추상화

  • Received : 2018.04.23
  • Accepted : 2018.09.27
  • Published : 2018.12.01

Abstract

In this paper, we present a non-photorealistic rendering technique that automatically delivers a stylized abstraction of a photograph with DoF(Depth of field). Our approach is a new filtering method that efficiently classifies DoF regions using RGB channels and automatically adjusts the color abstraction and extracted line quality based on this classification. This DoF-based filtering is simple, fast, and easy to implement and significantly improves the abstraction performance in terms of feature enhancement and stylization.

본 논문에서는 피사계 심도(DoF, Depth of field)가 포함된 사진을 자동으로 추상화 시켜주는 비 사실적 렌더링(NPR, Non-photorealistic rendering) 기술을 제안한다. 우리의 접근 방식은 RGB 채널을 이용하여 DoF 영역을 효율적으로 분류하고, DoF 크기에 따라 색상을 추상화하며, 라인의 두께를 자동으로 조절함으로 새롭게 필터링 하는 기술이다. DoF기반 필터링 방식은 성능과 디자인 관점에서 추상화의 품질을 크게 개선시켰으며, 간단하고 빨라 구현하기 쉽고, 사진으로부터 추상화나 일러스트레이션을 제작할 때 원본 사진이 갖고 있는 DoF의 특징과 스타일을 효율적으로 잘 표현한다.

Keywords

References

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