대한전자공학회논문지SP (Journal of the Institute of Electronics Engineers of Korea SP)

대한전자공학회 (The Institute of Electronics and Information Engineers)
권호 표지

3차원 메쉬의 면적 정보를 이용한 효과적인 잡음 제거

An effective filtering for noise smoothing using the area information of 3D mesh

  • 현대환 (중앙대학교 첨단영상대학원 영상공학과) ;
  • 최종수 (중앙대학교 첨단영상대학원 영상공학과)
  • Hyeon, Dae-Hwan (The Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang University) ;
  • Choi, Jong-Soo (The Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang University)
  • 발행 : 2007.03.25
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

본 논문에서는 카메라 자동 교정을 통한 3차원 재구성 과정에서 생기는 오차로 인해 포함되는 잡음을 특성에 따라 효과적으로 제거하여 정교한 3차원 데이터를 얻기 위한 방법을 제안한다. 기존의 잡음 평활화 과정은 잡음 때문에 면적이 큰 메쉬는 3차원으로 재구성하는데 문제점이 존재한다. 제안한 알고리즘은 메쉬의 면적이 중요하기 때문에 취득된 3차원 데이터는 불필요한 삼각형 메쉬들을 사전에 제거하는 전처리 과정이 필요하다. 본 연구는 3차원 메쉬의 면적 정보를 이용하여 잡음의 특성을 분석하고, 그 특성에 따라 피크 잡음과 가우스 잡음을 분리하여 효과적으로 잡음을 제거한다. 본 알고리즘의 성능은 재구성 데이터에 대한 정량적인 비교 분석을 통해 기존의 메쉬 평활화 방법보다 더 정교한 3차원 데이터를 얻음을 확인하였다.

This paper proposes method to get exquisite third dimension data removing included noise by error that occur in third dimension reconstruction through camera auto-calibration. Though reconstructing third dimension data by previous noise removing method, mesh that area is wide is happened problem by noise. Because mesh's area is important, the proposed algorithm need preprocessing that remove unnecessary triangle meshes of acquired third dimension data. The research analyzes the characteristics of noise using the area information of 3-dimensional meshes, separates a peek noise and a Gauss noise by its characteristics and removes the noise effectively. We give a quantitative evaluation of the proposed preprocessing filter and compare with the mesh smoothing procedures. We demonstrate that our effective preprocessing filter outperform the mesh smoothing procedures in terms of accuracy and resistance to over-smoothing.

키워드

References

  1. H. S. Sawhney, Y. Guo, J. Asmuth and R. Kumar, 'Multi-View 3D Estimation and Applications to Match Move', In proc. IEEE MVIEW, pp.21-28, 1999
  2. S. Gibson, J. Cook, T.Howard, R. Hubbold and D.Oram, 'Accurate Camera Calibration for Off-line, Video-Based Augmented Reality', In proc. IEEE and ACM ISMAR, Darmstadt, Germany, Sep. 2002
  3. Zhengyou ZHANG, “A Robust Technique for Matching Two Uncalibrated Images Through the Recovery of the Unknown Epipolar Geometry”, Technical Report, May, 1994
  4. P. Smith, D. Sinclair, R. Cipolla and K. Wood, 'Effective corner matching', BMVC, September 1998
  5. A.Chiuso, P.Favaro, H.Jin and S.Soatto, 'Structure from motion causally integrated over time', IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24 Issue: 4, pp. 523 -535, April 2002 https://doi.org/10.1109/34.993559
  6. Azarbayejani A., Pentland A.P., 'Recursive estimation of motion, structure, and focal length', IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume: 17 Issue: 6, pp. 562 -575, June 1995 https://doi.org/10.1109/34.387503
  7. B. Triggs, 'Autocalibration and the absolute quadric', Proc. Conference on Computer Vision and Pattern Recognition, IEEE Computer Soc. Press, pp. 609-614, 1997
  8. A. Heyden, K. Astrom, 'Euclidean Reconstruction from Constant Intrinsic Parameters', Proc. 13th International Conference on Pattern Recognition, IEEE Computer Soc. Press, pp. 339-343, 1996
  9. R. Hartley, J.L. Mundy, A. Zisserman, and D. Forsyth (eds.), 'Euclidean reconstruction from uncalibrated views', Applications of Invariance in Computer Vision, Lecture Notes in Computer Science , Vol. 825, Springer-Verlag, pp. 237-256, 1994
  10. Marc Pollefeys, 'Tutorial on 3D modeling from images', Dublin, Ireland In conjunction with ECCV, Lecture Notes, CH. 6, 26 June 2000
  11. Richard N. Ellson, Joseph H. Nurre, 'A new approach for modeling and smoothing of scattered 3D data', Proc. SPIE, Three- Dimensional Image Capture and Applications, Vol. 3313, pp. 168-177, 1998
  12. Yutaka Ohtake, Alexander Belyaev, Ilia Bogaevski, 'Mesh regularization and adaptive smoothing', Computer-Aided Design , Vol. 33, pp. 789-800, 2001
  13. G. Taubin, 'Linear anisotropic mesh filtering', IBM Research Report, October 2001
  14. Tasdizen, Whitaker, Burchard, Osher, 'Geometric surface smoothing via anisotropic diffusion of normals', Proceedings of the conference on Visualization , pp. 125-132, November 2002
  15. R. Klette, P. Zamperori, 'Handbook of Image Proceedings Operators', John Wileys & Sons, 2001