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The 3D Geometric Information Acquisition Algorithm using Virtual Plane Method

가상 평면 기법을 이용한 3차원 기하 정보 획득 알고리즘

  • 박상범 (숭실대학교 정보통신전자공학부) ;
  • 이찬호 (현대중공업 기계전기연구소) ;
  • 오종규 (현대중공업 기계전기연구소) ;
  • 이상훈 (현대중공업 기계전기연구소) ;
  • 한영준 (숭실대학교 정보통신전자공학부) ;
  • 한헌수 (숭실대학교 정보통신전자공학부)
  • Published : 2009.11.01

Abstract

This paper presents an algorithm to acquire 3D geometric information using a virtual plane method. The method to measure 3D information on the plane is easy, because it's not concerning value on the z-axis. A plane can be made by arbitrary three points in the 3D space, so the algorithm is able to make a number of virtual planes from feature points on the target object. In this case, these geometric relations between the origin of each virtual plane and the origin of the target object coordinates should be expressed as known homogeneous matrices. To include this idea, the algorithm could induce simple matrix formula which is only concerning unknown geometric relation between the origin of target object and the origin of camera coordinates. Therefore, it's more fast and simple than other methods. For achieving the proposed method, a regular pin-hole camera model and a perspective projection matrix which is defined by a geometric relation between each coordinate system is used. In the final part of this paper, we demonstrate the techniques for a variety of applications, including measurements in industrial parts and known patches images.

Keywords

References

  1. 신강호, 김계국, 'TV 영상의 3차원 변환을 위한 공간분석 알고리즘에 관한 연구,' 한국컴퓨터정보학회, vol. 7, no. 4, 2002
  2. Oliver Grall, 'A combined studio production system for 3D capturing of live action and immersive actor feedback,' IEEE Trans. Circuits and System for Video Technology, vol.14, no.3, 2004 https://doi.org/10.1109/TCSVT.2004.823397
  3. R. Zhang, P. Tsai, J. E Cryer, and M. Shah, 'Shape from Shading: A survey,' IEEE Trans PAMI, vol. 21, no. 8, pp. 690-706, 1999 https://doi.org/10.1109/34.784284
  4. J. Garding, 'Direct estimation of shape from texture,' IEEE Trans. PAM, vol. 15, no. 11, pp. 1202-1208, 1993 https://doi.org/10.1109/34.244682
  5. T. Matsuyama, X. Wu, T. Takai, and T. Wada, 'Real-time dynamic 3-D object shape reconstruction and high-fidelity texture mapping for 3-D video,' IEEE Trans. CSVT, vol. 14, no. 3, pp. 357-369, 2004 https://doi.org/10.1109/TCSVT.2004.823396
  6. W. E. L. Grimson, 'Computational experiments with a feature based algorithm,' IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 7, no. I, pp. 17-34, 1985 https://doi.org/10.1109/TPAMI.1985.4767615
  7. T. Kanade, 'A stereo matching algorithm with an adaptive window: Theory and experiment,' IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 16, no. 9, pp. 920-932, 1994 https://doi.org/10.1109/34.310690
  8. D. G. Lowe, 'Distinctive image feature from scale invariant Keypoints,' International journal of Computer Vision, vol. 60, no. 2, pp. 99-110, 2004 https://doi.org/10.1023/B:VISI.0000029664.99615.94
  9. W. Zhang and J. Kosecka, 'Image based localization in urban environments,' in Proceedings of the International Symposium on 3D Data Processing, Visualization, and Transmission, pp. 33-40, 2006
  10. http://visionlab.ssu.ac.kr/extlinklforcepsb/knownobject.avi http://visionlab.ssu.ac.kr/extlinklforcepsblknownpatches.avi