PERSPECTIVE-THREE-POINT (P3P) BY DETERMINING THE SUPPORT PLANE

Zhaozheng Hu, Takashi Matsuyama

2011

Abstract

This paper presents a new approach to solve the classic perspective-three-point (P3P) problem. The basic conception behind is to determine the support plane, which is defined by the three control points. Computation of the plane normal is formulated as searching for the maximum likelihood on the Gaussian hemisphere by exploiting the geometric constraints of three known angles and length ratios from the control points. The distances of the control points are then computed from the normal and the calibration matrix by homography decomposition. The proposed algorithm has been tested with real image data. The computation errors for the plane normal and the distances are less than 0.35 degrees, and 0.8cm, respectively, within 1~2m camera-to-plane distances. The multiple solutions to P3P problem are also illustrated.

References

  1. Fischler, M., and Bolles, R. (1981). Random sample consensus, Communications of the ACM, Vol. 24, No. 6, pp.381-395
  2. Gao, X., Hou, X., Tang, J., Cheng, H. (2003). Complete solution classification for the perspective-three-point problem, IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 25, No. 8, pp. 930-943
  3. Hartley, R., and Zisserman, A. (2000). Multiple view geometry in computer vision, Cambridge, UK: Cambridge University Press, 2nd Edition.
  4. Hu, Z., and Matsuyama, T. (2010). A generalized computation model for plane normal recovery by searching on Gaussian hemisphere, the Third International Conference on Computer and Electricity (ICCEE 2010), pp.145-149
  5. Liebowitz, D., and Zisserman, A. (1998). Metric rectification for perspective images of planes, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.482-488
  6. Moreno-Noguer, F., Lepetit, V., and Fua, P. (2007). Accurate non-iterative O(n) solution to the PnP problem. IEEE 11th International Conference on Computer Vision, pp. 1-8
  7. Vigueras, F., HerÁandez, A., and Maldonado, I. (2009). Iterative linear solution of the perspective-n-point problem using unbiased statistics, Eighth Mexican International Conference on Artificial Intelligence, Guanajuato, Mexico, pp.59-64
  8. Wolfe, W., Mathis, D., Sklair, C., Magee, M. (1991). The perspective view of 3 Points, IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 13, No. 1, pp.66-73
  9. Wu, Y., Hu, Z. (2006). PnP problem revisited. Journal of Mathematical Imaging and Vision, Vol. 24, No. 1, pp. 131-141
  10. Zhang, C., Hu, Z. (2006). Why is the danger cylinder dangerous in the P3P problem? Acta Automatiica Sinica, Vol. 32, No. 4, pp.504-511
  11. Zhang, Z. (2000). A flexible new technique for camera calibration, IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol.22, No. 11, pp.1330-1334
Download


Paper Citation


in Harvard Style

Hu Z. and Matsuyama T. (2011). PERSPECTIVE-THREE-POINT (P3P) BY DETERMINING THE SUPPORT PLANE . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011) ISBN 978-989-8425-47-8, pages 119-124. DOI: 10.5220/0003320301190124


in Bibtex Style

@conference{visapp11,
author={Zhaozheng Hu and Takashi Matsuyama},
title={PERSPECTIVE-THREE-POINT (P3P) BY DETERMINING THE SUPPORT PLANE},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)},
year={2011},
pages={119-124},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003320301190124},
isbn={978-989-8425-47-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)
TI - PERSPECTIVE-THREE-POINT (P3P) BY DETERMINING THE SUPPORT PLANE
SN - 978-989-8425-47-8
AU - Hu Z.
AU - Matsuyama T.
PY - 2011
SP - 119
EP - 124
DO - 10.5220/0003320301190124