Conference paper

PŘIBYL Bronislav, ZEMČÍK Pavel and ČADÍK Martin. Camera Pose Estimation from Lines using Plücker Coordinates. In: Proceedings of the British Machine Vision Conference (BMVC 2015). Swansea: The British Machine Vision Association and Society for Pattern Recognition, 2015, pp. 1-12. ISBN 978-1-901725-53-7. Available from:
Publication language:english
Original title:Camera Pose Estimation from Lines using Plücker Coordinates
Title (cs):Odhad pózy kamery z přímek parametrizovaných Plückerovými souřadnicemi
Proceedings:Proceedings of the British Machine Vision Conference (BMVC 2015)
Conference:British Machine Vision Conference (BMVC) 2015
Place:Swansea, GB
Publisher:The British Machine Vision Association and Society for Pattern Recognition
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iconCamera-Pose-Estimation-from-Lines-using-Plucker-Coordinates_abstract.pdf1-page abstract74,1 KB2015-09-14 14:13:12
iconCamera-Pose-Estimation-from-Lines-using-Plucker-Coordinates_paper.pdfpaper459 KB2015-09-14 14:13:12
iconCamera-Pose-Estimation-from-Lines-using-Plucker-Coordinates_poster.pdfposter1,9 MB2015-09-14 14:13:14
iconCamera-Pose-Estimation-from-Lines-using-Plucker-Coordinates_supp.zipsupplementary material13,2 MB2016-01-14 13:29:20
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Camera Pose Estimation, Plücker Coordinates, Linear Least Squares, Direct Linear Transformation, Algebraic Outlier Rejection
Correspondences between 3D lines and their 2D images captured by a camera are often used to determine position and orientation of the camera in space. In this work, we propose a novel algebraic algorithm to estimate the camera pose. We parameterize 3D lines using Plücker coordinates that allow linear projection of the lines into the image. A line projection matrix is estimated using Linear Least Squares and the camera pose is then extracted from the matrix. An algebraic approach to handle mismatched line correspondences is also included. The proposed algorithm is an order of magnitude faster yet comparably accurate and robust to the state-of-the-art, it does not require initialization, and it yields only one solution. The described method requires at least 9 lines and is particularly suitable for scenarios with 25 and more lines, as also shown in the results.

The Matlab code of the proposed method is available for download.

   author = {Bronislav P{\v{r}}ibyl and Pavel Zem{\v{c}}{\'{i}}k and
	Martin {\v{C}}ad{\'{i}}k},
   title = {Camera Pose Estimation from Lines using Pl{\"{u}}cker
   pages = {1--12},
   booktitle = {Proceedings of the British Machine Vision Conference (BMVC
   year = {2015},
   location = {Swansea, GB},
   publisher = {The British Machine Vision Association and Society for
	Pattern Recognition},
   ISBN = {978-1-901725-53-7},
   doi = {10.5244/C.29.45},
   language = {english},
   url = {}

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