3-D Pose Estimation of an Elliptic Object Using Two Coplanar Points

두 개의 공면점을 활용한 타원물체의 3차원 위치 및 자세 추정

  • 김헌희 (광운대학교 예술로봇연구소) ;
  • 박광현 (광운대학교 로봇학부) ;
  • 하윤수 (한국해양대학교 IT공학부)
  • Received : 2011.10.11
  • Accepted : 2012.06.27
  • Published : 2012.07.25

Abstract

This paper presents a 3-D pose (position and orientation) estimation method for an elliptic object in 3-D space. It is difficult to resolve the problem of determining 3-D pose parameters with respect to an elliptic feature in 3-D space by interpretation of its projected feature onto an image plane. As an alternative, we propose a two points-based pose estimation algorithm to seek the 3-D information of an elliptic feature. The proposed algorithm determines a homogeneous transformation uniquely for a given correspondence set of an ellipse and two coplanar points that are defined on model and image plane, respectively. For each plane, two triangular features are extracted from an ellipse and two points based on the polarity in 2-D projection space. A planar homography is first estimated by the triangular feature correspondences, then decomposed into 3-D pose parameters. The proposed method is evaluated through a series of experiments for analyzing the errors of 3-D pose estimation and the sensitivity with respect to point locations.

Acknowledgement

Supported by : 한국연구재단

References

  1. L. Wenjing, G. Bebis, and N. G. Bourbakis, "3-D object recognition using 2-D views," IEEE Transactions on Image Processing, vol. 17, pp. 2236-2255, 2008. https://doi.org/10.1109/TIP.2008.2003404
  2. D. Forsyth, J. L. Mundy, A. Zisserman, C. Coelho, A. Heller, and C. Rothwell, "Invariant descriptors for 3-D object recognition and pose," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 13, pp. 971-991, 1991. https://doi.org/10.1109/34.99233
  3. R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, Cambridge University Press, 2004.
  4. R. Safaee-Rad, I. Tchoukanov, K. C. Smith, and B. Benhabib, "Three-dimensional location estimation of circular features for machine vision," IEEE Transactions on Robotics and Automation, vol. 8, pp. 624-640, 1992. https://doi.org/10.1109/70.163786
  5. K. Kanatani and W. Liu, "3-D Interpretation of Conics and Orthogonality," CVGIP: Image Understanding, vol .58, pp. 286-301, 1993. https://doi.org/10.1006/ciun.1993.1043
  6. 한광수, 한영준, 한헌수, "선분세그먼트 기반 Randomized Hough Transformation", 대한전자공학회, 대한전자공학회논문지-SC, 제 44권, 제 6호, 11-20쪽, 2007년.
  7. 박상국, 김성용, 김수중, "일반 타원의 검출을 위한 광학적 Hough변환의 적용", 대한전자공학회, 전자공학회논문지-SD, 제37권, 제8호, 67-75쪽, 2000년.
  8. 김헌희, 박광현, 하윤수, "공면 점을 포함한 원형 특징의 3차원 자세 및 위치 추정", 대한전자공학회, 전자공학회 논문지-SC, 제 48권, 제5호, 2011 년.
  9. R. Safaee-Rad, K. C. Smith, B. Benhabib, and I. Tchoukanov, "Constraints on quadratic curves under perspective projection," in Proc. of IEEE Conf. on Systems, Man, and Cybernetics, vol. 1, pp. 57-62, 1991.
  10. A. Sugimoto, "A linear algorithm for computing the homography from conics in correspondence," Journal of Mathematical Imaging and Vision, vol. 13, pp. 115-130, 2000. https://doi.org/10.1023/A:1026571913893
  11. J. Kannala, M. Salo, and J. Heikkilä, "Algorithms for computing a planar homography from conics in correspondence," in Proc. of British Machine Vision Conference, pp. 77-78, 2006.
  12. C. Conomis, "Conics-based homography estimation from invariant points and pole-polar relationships," in Proc. of International Symposium on 3D Data Processing, Visualization, and Transmission, pp. 908-915, 2006.
  13. A. Gupta, J. J. Little, and R. J. Woodham, "Using line and ellipse features for rectification of broadcast hockey video," in Porc. of Canadian Robot Vision(CVR '11), pp. 32-39, 2011.
  14. Z. Zhang. "A flexible new technique for camera calibration," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 11, pp. 1330-1334, 2000. https://doi.org/10.1109/34.888718
  15. Y. Ma, S. Soatto, J. Kosecka, and S. Sastry, An invitation to 3-D vision, Springer, 2004.