전자공학회논문지 (Journal of the Institute of Electronics and Information Engineers)

  • 제51권6호
  • /
  • Pages.102-109
  • /
  • 2014
  • /
  • 2287-5026(pISSN)
  • /
  • 2288-159X(eISSN)
대한전자공학회 (The Institute of Electronics and Information Engineers)
권호 표지
DOI QR코드

DOI QR Code

입자추적기반의 불꽃 모델링 기법

Fireworks Modeling Technique based on Particle Tracking

  • 조창우 (고려대학교 영상정보처리) ;
  • 김기현 (고려대학교 영상정보처리) ;
  • 정창성 (고려대학교 영상정보처리)
  • Cho, ChangWoo (Division of Internet & Multimedia Engineering, Korea University) ;
  • Kim, KiHyun (Division of Internet & Multimedia Engineering, Korea University) ;
  • Jeong, ChangSung (Division of Internet & Multimedia Engineering, Korea University)
  • 투고 : 2014.04.07
  • 심사 : 2014.05.26
  • 발행 : 2014.06.25
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

입자 시스템은 물리적 현상을 모델링하기 위해 자주 사용된다. 특히, 3차원 공간에서의 풍경, 구름, 파도, 안개, 비, 눈, 불꽃 등의 모델링에 적합하다. 시뮬레이션 모델링에는 다양한 전통적인 방법이 존재하지만 본 논문에서는 입자 시스템을 사용하여 불꽃 입자 추적을 기반으로 한 새로운 불꽃 모델링 기법을 제시하였다. 이 방법은 불꽃 추적을 통해 발사 및 분산한 입자들을 인식하고, 스테레오 기법을 이용함으로써 3D 깊이 값을 구하여 비교적 정확한 3차원적 위치를 추출 할 수 있다. 그러므로 불꽃 입자의 위치, 속도, 색상 및 수명 등의 파라메타를 불꽃 추적을 통해 산출하였고 이를 이용하여 3D 시뮬레이션을 재연할 수 있다. 본 연구는 빠른 입자 추출 및 노이즈에 의한 허위 입자 추출을 방지하기 위해 관심 영역을 사용하였고, 발사 단계에서 견고성을 향상시키기 위해 칼만 필터를 사용하였다. 또한, 입자의 이동 방향을 예측하여 효율적인 추적을 위해 입자의 최대 이동 범위를 고려한 새로운 불꽃 입자 추적 방법을 제안 하였다. 그리고 3D 공간에서 입자의 속도는 불꽃의 회전 각도를 찾음으로써 얻어 질 수 있다. 본 논문에서는 불꽃축제에서 자주 사용되는 구, 원, 국화, 하트 이 네 가지 불꽃 유형에 대하여 각각 모델링에 필요한 파라메타를 불꽃 추적을 통해 구하였고 추적에 대한 속도와 정확도를 측정하였다.

A particle system is used for modeling the physical phenomenon. There are many traditional ways for simulation modeling which can be well suited for application including the landscapes of branches, clouds, waves, fog, rain, snow and fireworks in the three-dimensional space. In this paper, we present a new fireworks modeling technique for modeling 3D firework based on Firework Particle Tracking (FPT) using the particle system. Our method can track and recognize the launched and exploded particle of fireworks, and extracts relatively accurate 3D positions of the particles using 3D depth values. It can realize 3D simulation by using tracking information such as position, speed, color and life time of the firework particle. We exploit Region of Interest (ROI) for fast particle extraction and the prevention of false particle extraction caused by noise. Moreover, Kalman filter is used to enhance the robustness in launch step. We propose a new fireworks particle tracking method for the efficient tracking of particles by considering maximum moving range and moving direction of particles, and shall show that the 3D speeds of particles can be obtained by finding the rotation angles of fireworks. Also, we carry out the performance evaluation of particle tracking: tracking speed and accuracy for tracking, classification, rotation angle respectively with respect to four types of fireworks: sphere, circle, chrysanthemum and heart.

키워드

참고문헌

  1. J. Grudzinski and A. Debowski, "Clouds and atmospheric phenomena simulation in real-time 3D graphics," Springer-Verlag Berlin Heidelberg, 2007.
  2. V. Biri, S. Michelin and D. Arques, "Real-time animation of realistic fog," 13th Eurographics workshop on rendering, Pisa, Italy, 2002.
  3. R. Fedkiw, J. Stam and H. W. Jensen, "Visual simulation of smoke," SIGGRAPH 2001, Computer Graphics Proceedings. ACM Press/ACM SIGGRAPH, pp. 15-22, 2001.
  4. G. P. Lu, D. J. DePaolo, Q. Kang and D. Zhang, "Lattice boltzmann simulation of snow crystal growth in clouds," J. Geophy. Res. 114, D07305, 2009.
  5. E. Cerezo and F. J. Seron, "Rendering natural water: merging computer graphics with physics and biology," Advances in Modelling, Animation and Rendering (Proceedings of Computer Graphics International 2002), pp. 481-498, 2002.
  6. Sanandanan and Somasekaran, "Using particle system to simulate real-time fire," the university of Western Australia, Australia, 2005.
  7. W. Reeves, "Particle systems - A technique for modeling a class of fuzzy objects," Computer Graphics 17, 3. pp. 359-376, July 1983. https://doi.org/10.1145/964967.801167
  8. T. Loke, D. Tan and H. Seah, "Rendering fireworks displays," IEEE Computer Graphics and Applications, pp. 33-43, May 1992.
  9. J. Y. Ding, P. Li and S. K. Li, "Dynamic simulation for fireworks display based on OpenGL," Computer Engineering Vol.28, No.4, pp.240-241, April 2002.
  10. H. Xiao and C. L. He, "Real-time simulation of fireworks based on GPU and particle system," 2009 First International Workshop on Education Technology and Computer Science, Mar 2009.
  11. P. Fua. "A parallel stereo algorithm that produce dense depth maps and preserves image features," Machine Vision Applications, pp.35-49, 1993.
  12. Y.S Kang and Y.S Ho, "Depth Generation Method Using Multiple Color and Depth Cameras", Journal of The Institute of Electronics Engineers of Korea, Vol. 48-SP, No.3, pp.13-18, 2011.
  13. H.H Jung, T.Y Kim and J. Lyou, "3D Image Construction Using Color and Depth Cameras", Journal of The Institute of Electronics Engineers of Korea, Vol. 49-SC, No.1, pp.1-7, 2012.
  14. M. I. Ribeiro, "Kalman and extended kalman filters: Concept, derivation and properties, institute for systems and robotics," Instituto Superior Tecnico, Av. Rovisco Pais, 1, February 2004.
  15. R. Kalman, "A new approach to linear filtering and prediction problems," Transactions of Journal Basic Engineering, ASME Series, D 82, pp. 35-45, 1960. https://doi.org/10.1115/1.3662552
  16. W. Dong, X. Zhang and C. Zhang, "Firework simulation based on particle system in virtual scene," International Conference on Multimedia Communications, Hong Kong, August 2010.
  17. P. Gargallo, E. Prados and P. Sturm, "Minimizing the reprojection error in surface reconstruction from images," IEEE International Conference on Computer Vision, Oct 2007.