Combining Line and Point Correspondences for Homography Estimation

@inproceedings{Dubrofsky2008CombiningLA,
  title={Combining Line and Point Correspondences for Homography Estimation},
  author={Elan Dubrofsky and Robert J. Woodham},
  booktitle={ISVC},
  year={2008}
}
This paper presents a method to extend the normalized direct linear transform (DLT) algorithm for homography estimation. Previously, only point correspondences were used. Now, line correspondences can be included as well. This extension is point-centric in that the lines are normalized to fit with the normalization used for points. Therefore, this method will be most useful if there are more point correspondences than line correspondences. The main contribution of this paper is the derivation… CONTINUE READING

Figures, Tables, and Topics from this paper.

Citations

Publications citing this paper.
SHOWING 1-10 OF 20 CITATIONS

On Line-based Homographies in Urban Environments

VIEW 4 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

Automatic initialization for broadcast sports videos rectification by Shervin

VIEW 6 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

A New Accurate and Fast Homography Computation Algorithm for Sports and Traffic Video Analysis

  • IEEE Transactions on Circuits and Systems for Video Technology
  • 2018
VIEW 1 EXCERPT
CITES METHODS

A Two-Point Method for PTZ Camera Calibration in Sports

  • 2018 IEEE Winter Conference on Applications of Computer Vision (WACV)
  • 2018

Image registration through self-correcting based on line segments

  • 2017 29th Chinese Control And Decision Conference (CCDC)
  • 2017
VIEW 1 EXCERPT
CITES METHODS

Multi-element ultrasound transducer positioning method in MR-guided phased HIFU system

  • 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)
  • 2017
VIEW 1 EXCERPT
CITES METHODS

References

Publications referenced by this paper.
SHOWING 1-5 OF 5 REFERENCES

Multiple View Geomerty in Computer Vision, 2nd edn

R. Hartley, A. Zisserman
  • Cambridge University Press, Cambridge
  • 2003
VIEW 12 EXCERPTS
HIGHLY INFLUENTIAL

In defense of the eight-point algorithm

R. Hartley
  • IEEE Transactions on Pattern Analysis and Machine Intelligence 19, 580–593
  • 1997
VIEW 1 EXCERPT

Good features to track

  • 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
  • 1994
VIEW 1 EXCERPT