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User-friendly 3D Object Reconstruction Method based on Structured Light in Ubiquitous Environments

유비쿼터스 환경에서 구조광 기반 사용자 친화적 3차원 객체 재구성 기법

  • Received : 2013.08.16
  • Accepted : 2013.11.13
  • Published : 2013.11.28

Abstract

Since conventional methods for the reconstruction of 3D objects used a number of cameras or pictures, they required specific hardwares or they were sensitive to the photography environment with a lot of processing time. In this paper, we propose a 3D object reconstruction method using one photograph based on structured light in ubiquitous environments. We use color pattern of the conventional method for structured light. In this paper, we propose a novel pipeline consisting of various image processing techniques for line pattern extraction and matching, which are very important for the performance of the object reconstruction. And we propose the optimal cost function for the pattern matching. Using our method, it is possible to reconstruct a 3D object with efficient computation and easy setting in ubiquitous or mobile environments, for example, a smartphone with a subminiature projector like Galaxy Beam.

3차원 공간에서 물체를 재구성하기 위하여 제안된 기존 기법들은 여러 개의 카메라를 사용하거나 여러장의 사진을 촬영하여 물체를 재구성하기 때문에 특정한 하드웨어를 필요로 하거나 촬영 장소에 민감하고 시간이 오래 걸린다는 단점이 있다. 본 논문에서는 유비쿼터스 환경에서 구조광 기법을 이용하여 한 장의 사진의 정보로부터 3차원 물체를 재구성하는 방법을 제안한다. 구조광 기법 적용을 위한 칼라 패턴은 기존연구에서 제안된 것을 사용한다. 본 논문에서는 실제로 객체 재구성 성능에 매우 중요한 줄무늬 패턴 추출과 줄무늬 패턴 매칭에 다양한 영상 처리 기법들로 구성된 파이프라인을 새롭게 제안하고, 패턴 매칭을 위한 최적의 비용 함수를 제안한다. 제안 기법을 통하여 갤럭시 빔과 같은 초소형 프로젝터를 탑재한 스마트폰과 같은 유비쿼터스 혹은 모바일 환경에서 적은 계산 복잡도와 간단한 환경 설정으로 3차원 물체를 재구성하는 것이 가능하다.

Keywords

References

  1. T. Acharya and A. Ray, Image Processing - Principles and Applications, Wiley InterScience, 2006.
  2. D. Scharstein and R. Szeliski, "A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms," International Journal of Computer Vision, Vol.47, No.1, pp.7-42, 2002. https://doi.org/10.1023/A:1014573219977
  3. J. Turner, M. L. Braunstein, and G. J. Andersen, "Relationship between Binocular Disparity and Motion Parallax in Surface Detection," Percept Psychophys, Vol.59, No.3, pp.370-380, 1997. https://doi.org/10.3758/BF03211904
  4. J. Posamer and M. Altschuler, "Surface Measurement by Space-Encoded Projected Beam System," Computer Graphics and Image Processing, Vol.18, No.1, pp.1-17, 1982. https://doi.org/10.1016/0146-664X(82)90096-X
  5. D. Capsi, N. Kiryati, and J. Shamir, "Range Imaging with Adaptive Color Structured Light," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.20, No.5, pp.470-480, 1998. https://doi.org/10.1109/34.682177
  6. J. Pages, J. Salvi, R. Gracia, and C. Matabosch, "Overview of Coded Light Projection Techniques for Automatic 3D Profiling," IEEE Int'l Conf. on Robotics and Automation, pp.133-138, 2003.
  7. D. Lanman and G. Taubin, Build Your Own 3D Scanner: Optical Triangulation for Beginners, Courses on Siggraph, 2009.
  8. J. Beraldin, F. Blais, L. Cournoyer, G. Godin, and M. Rioudx, "Active 3D Sensing," NRC Technical Report, 2000.
  9. S. Ryusuke, "Dense 3D Reconstruction Method Using a Single Pattern for Fast Moving Object," IEEE Computer Vision 12th Int'l Conf., pp.1779-1786, 2009.
  10. H. Fredricksen, "The Lexicographically Least De Brujin Cycle," Journal of Combinatorial Theory, Vol.9, No.1, pp.509-510, 1970.
  11. J. Geng, "Structured-light 3D surface imaging: a tutorial," Advances in Optics and Photonics, Vol.3, No.2, pp.128-160, 2011. https://doi.org/10.1364/AOP.3.000128
  12. U. Kthe, "Edge and Junction Detection with an Improved Structure Tensor," Pattern Recogniton Proc. of 25th DAGM Symposium, pp.25-32, 2003.
  13. Roger Y. Tsai, "An Efficient and Accurate Camera Calibration Technique for 3D Machine Vision," Proc. of IEEE Conf. on Computer Vision and Pattern Recognition, pp.364-374, 1986.
  14. 서정구, 강의선, "FOV 모델과 2D 패턴을 이용한 왜곡 중심 추정 기법", 한국콘텐츠학회논문지, 제13권, 제8호, pp.11-19, 2013. https://doi.org/10.5392/JKCA.2013.13.08.011
  15. R. Hartley, Multiple View Geometry in Computer Vision, Cambridge Univ Press, pp.155-157.
  16. http://www.trimensional.com/

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  1. 3D Accuracy Analysis of Mobile Phone-based Stereo Images vol.19, pp.5, 2014, https://doi.org/10.5909/JBE.2014.19.5.677