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Efficient Non-photorealistic Rendering Technique in Single Images and Video

영상 동영상에서의 효율적인 비사실적 렌더링

  • 손태일 (중앙대학교 첨단영상대학원 영상학과) ;
  • 박경주 (중앙대학교 첨단영상대학원 영상학과)
  • Received : 2012.01.25
  • Accepted : 2012.06.18
  • Published : 2012.08.31

Abstract

The purpose of this study was to present a non-photorealistic rendering technique that is efficient in single images and moving images. In case of single images, they could be processed in a real-time base by realizing flow-based DoG filter and bilateral filter, which have been frequently used in the single image NPR technique recently, in the CUDA environment. In case of moving images, the investigator presented not the existing method of NPR moving images which generating images by applying the single image NPR technique to every frame, but the method of using the single image NPR technique in the first frame and stylizing it, and then of using the motion vector-based pixel mapping in the second frame on and copying the bright values of pixels that move on the frame into the location of next frame's motion vector, thus reducing unnecessary volume of calculation and maintaining the consistency between frames. In this study, the performance of this method was proved via an experiment.

본 연구에서는 단일영상과 동영상에서의 효율적인 비사실적 렌더링 기법을 제안한다. 단일영상의 경우에는 최근 단일영상 NPR 기법에서 많이 사용되는 플로우 기반 DoG 필터와 Bilateral 필터를 CUDA 환경에서 구현하여 실시간 처리가 가능하게 한다. 또한 동영상의 경우에는 기존의 NPR 동영상 방법인 매 프레임마다 단일영상 NPR 기법을 적용하여 생성하는 방법이 아닌 첫 프레임은 단일영상에 적용되는 NPR기법을 사용하여 스타일화 하고, 다음 프레임부터는 움직임 벡터를 기반으로 한 픽셀 맵핑을 사용하여 이전 프레임에서 움직임이 있는 픽셀의 밝기 값을 다음 프레임의 움직임 벡터 위치로 복사함으로써 불필요한 계산량을 줄이고, 프레임 간의 일관성 또한 유지시키는 방법을 제안한다. 본 연구에서는 실험을 통하여 그 성능을 증명하였다.

Keywords

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