• Title/Summary/Keyword: 광선 투사법

Search Result 22, Processing Time 0.019 seconds

Smoke Rendering Method in Post-processing for Safety-Training Contents (안전 훈련 콘텐츠에 적합한 포스트 프로세싱 단계에서의 연기 렌더링 방법)

  • Park, Sanghyun
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.26 no.11
    • /
    • pp.1644-1652
    • /
    • 2022
  • In the case of safety training where practical training is impossible due to risk problems, training contents using realistic media such as virtual reality or augmented reality are becoming a new alternative. In this paper, we propose a smoke modeling method that can be applied to safety-training contents implemented with realistic media technology. When an accident occurs in a hazardous area such as a petrochemical plant, visibility is not secured due to gas leakage and fire. In order to create such a situation, it is important to realistically express smoke. The proposed method is a smoke model implementation technique that can be effectively applied to the background of complex passages and devices such as petrochemical plants. In the proposed method, the smoke is expressed using volumetric rendering in the post-processing stage for the resulting image of scene rendering. Implementation results in the background of the factory show that the proposed method produces models that can express the smoke realistically.

Realistic and Fast Depth-of-Field Rendering in Direct Volume Rendering (직접 볼륨 렌더링에서 사실적인 고속 피사계 심도 렌더링)

  • Kang, Jiseon;Lee, Jeongjin;Shin, Yeong-Gil;Kim, Bohyoung
    • The Journal of Korean Institute of Next Generation Computing
    • /
    • v.15 no.5
    • /
    • pp.75-83
    • /
    • 2019
  • Direct volume rendering is a widely used method for visualizing three-dimensional volume data such as medical images. This paper proposes a method for applying depth-of-field effects to volume ray-casting to enable more realistic depth-of-filed rendering in direct volume rendering. The proposed method exploits a camera model based on the human perceptual model and can obtain realistic images with a limited number of rays using jittered lens sampling. It also enables interactive exploration of volume data by on-the-fly calculating depth-of-field in the GPU pipeline without preprocessing. In the experiment with various data including medical images, we demonstrated that depth-of-field images with better depth perception were generated 2.6 to 4 times faster than the conventional method.