영상 동영상에서의 효율적인 비사실적 렌더링

초록

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.

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