3차원 형상 재구성을 위한 새로운 복셀 칼라링 기법

A New Voxel Coloring Method for 3D Shape Reconstruction

  • 예수영 (부산대학교 전자공학과) ;
  • 김효성 (부산대학교 전자공학과) ;
  • 주재흠 (부산가톨릭대학교 컴퓨터정보공학부) ;
  • 남기곤 (부산대학교 전자공학과)
  • Ye Sooyoung (Dept. of Electronics Engr., Pusan National University) ;
  • Kim Hyosung (Dept. of Electronics Engr., Pusan National University) ;
  • Joo Jaeheum (School of Computer Info. Engr., Catholic University of Pusan) ;
  • Nam Kigon (Dept. of Electronics Engr., Pusan National University)
  • 발행 : 2005.11.01

초록

본 논문에서는 3차원 형상 재구성을 위하여 기존 복셀 칼라링 기법의 색상 일관성에 대한 문턱값 문제를 해결하기 위한 새로운 복셀 칼라링 기법을 제안하였다. 제안 기법에서는 중심카메라의 광선분위에 있는 내부 복셀의 색상 일광성을 비교함으로써 최적의 문턱값을 결정하였다. 즉, 표면 복셀에 대한 색상 일관성과 내부 복셀의 색상 일관성 값을 비교함으로써 표면 복셀에 대한 최적의 문턱값을 찾아가도록 하였다. 또한 그래프 절단 기법을 적용하여 주위 복셀을 제거함으로써 표면 잡음을 감소시켰다. 제안된 방법은 기존의 알고리듬보다 빠르고 정확하게 3차원형상을 재구성 할 수 있었다.

We propose an optimal thresholding method for the voxel coloring in the reconstruction of a 3D shape. Our purposed method is a new approach to resolve the trade-off error of the threshold value on determining the photo-consistency in the conventional method. Optimal thresholding value is decided to compare the photo-consistency of a surface with inside voxel on the optic ray of the center camera. As iterating the process of the vokels, the threshold is approached to the optimal value for the individual surface voxel. And also, graph cut method is reduced to the surface noise on eliminating neighboring voxel. To verify the proposed algorithm, we simulated in the virtual and real environment. It is advantaged to speed up and accuracy of a 3D face reconstruction by applying the methods of optimal threshold and graph as compare with conventional algorithms.

키워드

참고문헌

  1. M. Potmesil, 'Generating octree models of 3D objects from their silhouettes in a sequence of image,' Computer Vision, Graphics, and Image Processing, vol. 40, pp. 1-29, 1987 https://doi.org/10.1016/0734-189X(87)90053-3
  2. R. Szeliski, 'Rapid Octree Construction from Image Sequences,' Computer Vision, Graphics, and Image Processing, vol. 58, no. 1, pp. 23-32, Jul. 1993 https://doi.org/10.1006/ciun.1993.1029
  3. S. M. Seitz and C. R. Dyer, 'Photorealistic Scene Reconstruction by Voxel Coloring,' Proc. Computer Vision and Pattern Recognition Conf., pp. 1067-1073, 1997
  4. W. B. Culbertson, T. Malzbender and G. Slabaugh, 'Generalized voxel coloring,' Proc. of the ICCV, pp. 100-115, Sep. 1999
  5. G. Slabaugh, W. Culbertson, T. Malzbender, M. Stevens and R. Schafer, 'Methods for volumetric reconstruction of visual scenes,' Int. J. of Computer Vision, vol. 57, no. 3, pp. 179-199, 2004 https://doi.org/10.1023/B:VISI.0000013093.45070.3b
  6. P. Eisert, E. Steinbach and B. Griod, 'Multi-hypothesis, volumetric reconstruction of 3-D objects from multiple calibrated camera views,' ICASSP'99, Phoenix, USA, pp. 3509-3512 , Mar. 1999 https://doi.org/10.1109/ICASSP.1999.757599
  7. P. Eisert, E. Steinbach and B. Griod, 'Automatic Reconstruction of stationary 3-D objects from multiple uncalibrated camera views,' IEEE Trans. on Circuits and Systems for Video Technology, vol. 10, no. 2, pp. 261-277, 2000 https://doi.org/10.1109/76.825726
  8. Y. Kuau and O. Sinram, 'Photorealistic Object Reconstruction Using Voxel Coloring And Adjusted Image Orientations,' ASPRS/ACSM/FIG -Conference, Washington DC., USA, 2002
  9. Y. Boykov and V. Kolmogorov, 'An Experimental Comparison of Min-Cut/ Max-Flow Algorithms for Energy Minimization in Vision,' IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 26, no. 9, pp. 1124-1137, Sep, 2004 https://doi.org/10.1109/TPAMI.2004.60
  10. V. Kolmogorov and R. Zabih, 'What Energy Functions can be Minimized via Graph Cuts?,' IEEE Trans. on Pattern Analysis and Machine Intelligence, Feb. 2004 https://doi.org/10.1109/TPAMI.2004.1262177