by Nora Horanyi, Zoltan Kato
Abstract:
We propose a novel method to compute the absolute pose of a generalized camera based on straight lines, which are common in urban environment. The only assumption about the imaging model is that 3D straight lines are projected via projection planes determined by the line and camera projection directions, ie correspondences are given as a 3D world line and its projection plane. Since modern cameras are frequently equipped with various location and orientation sensors, we assume that the vertical direction (\eg a gravity vector) is available. Therefore we formulate the problem in terms of 4 unknowns using 3D line - projection plane correspondences which yields a closed form solution. The solution can be used as a minimal solver as well as a least squares solver without reformulation. The proposed algorithm have been evaluated on various synthetic datasets as well as on real data. Experimental results confirm state of the art performance both in terms of quality and computing time.
Reference:
Nora Horanyi, Zoltan Kato, Generalized Pose Estimation from Line Correspondences with Known Vertical Direction, In Proceedings of International Conference on 3D Vision, Qingdao, China, pp. 1-10, 2017, IEEE.
Bibtex Entry:
@string{ic3dv="Proceedings of International Conference on 3D Vision"}
@InProceedings{Horanyi2017a,
author = {Nora Horanyi and Zoltan Kato},
title = {Generalized Pose Estimation from Line
Correspondences with Known Vertical Direction},
booktitle = ic3dv,
year = 2017,
pages = {1-10},
address = {Qingdao, China},
month = oct,
publisher = {IEEE},
pdf = {papers\3dv2017.pdf},
abstract = {We propose a novel method to compute the absolute
pose of a generalized camera based on straight
lines, which are common in urban environment. The
only assumption about the imaging model is that 3D
straight lines are projected via projection planes
determined by the line and camera projection
directions, \ie correspondences are given as a 3D
world line and its projection plane. Since modern
cameras are frequently equipped with various
location and orientation sensors, we assume that the
vertical direction (\eg a gravity vector) is
available. Therefore we formulate the problem in
terms of 4 unknowns using 3D line - projection plane
correspondences which yields a closed form
solution. The solution can be used as a minimal
solver as well as a least squares solver without
reformulation. The proposed algorithm have been
evaluated on various synthetic datasets as well as
on real data. Experimental results confirm state of
the art performance both in terms of quality and
computing time.}
}