Pose Estimation with Unknown Focal Length using Points, Directions and Lines
Kuang, Yubin LU and Åström, Karl LU
(2013)
IEEE International Conference on Computer Vision (ICCV), 2013
p.529-536
- Abstract
- In this paper, we study the geometry problems of estimating
camera pose with unknown focal length using combination
of geometric primitives. We consider points, lines
and also rich features such as quivers, i.e. points with one
or more directions. We formulate the problems as polynomial
systems where the constraints for different primitives
are handled in a unified way. We develop efficient polynomial
solvers for each of the derived cases with different
combinations of primitives. The availability of these solvers
enables robust pose estimation with unknown focal length
for wider classes of features. Such rich features allow for
fewer feature... (More) - In this paper, we study the geometry problems of estimating
camera pose with unknown focal length using combination
of geometric primitives. We consider points, lines
and also rich features such as quivers, i.e. points with one
or more directions. We formulate the problems as polynomial
systems where the constraints for different primitives
are handled in a unified way. We develop efficient polynomial
solvers for each of the derived cases with different
combinations of primitives. The availability of these solvers
enables robust pose estimation with unknown focal length
for wider classes of features. Such rich features allow for
fewer feature correspondences and generate larger inlier
sets with higher probability. We demonstrate in synthetic
experiments that our solvers are fast and numerically stable.
For real images, we show that our solvers can be used
in RANSAC loops to provide good initial solutions. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4249659
- author
- Kuang, Yubin
LU
and Åström, Karl
LU
- organization
- publishing date
- 2013
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Computer vision, pose, line, points, quiver, rich feature
- host publication
- [Host publication title missing]
- pages
- 8 pages
- publisher
- Computer Vision Foundation
- conference name
- IEEE International Conference on Computer Vision (ICCV), 2013
- conference location
- Sydney, Australia
- conference dates
- 2013-12-01 - 2013-12-08
- external identifiers
-
- scopus:84898791946
- language
- English
- LU publication?
- yes
- additional info
- The authoritative version of this paper will be available i IEEE Xplore.
- id
- defd3bac-a445-4938-b263-a44b59077039 (old id 4249659)
- alternative location
- http://www.cv-foundation.org/openaccess/content_iccv_2013/papers/Kuang_Pose_Estimation_with_2013_ICCV_paper.pdf
- date added to LUP
- 2016-04-04 11:27:51
- date last changed
- 2022-05-17 04:46:54
@inproceedings{defd3bac-a445-4938-b263-a44b59077039,
abstract = {{In this paper, we study the geometry problems of estimating<br/><br>
camera pose with unknown focal length using combination<br/><br>
of geometric primitives. We consider points, lines<br/><br>
and also rich features such as quivers, i.e. points with one<br/><br>
or more directions. We formulate the problems as polynomial<br/><br>
systems where the constraints for different primitives<br/><br>
are handled in a unified way. We develop efficient polynomial<br/><br>
solvers for each of the derived cases with different<br/><br>
combinations of primitives. The availability of these solvers<br/><br>
enables robust pose estimation with unknown focal length<br/><br>
for wider classes of features. Such rich features allow for<br/><br>
fewer feature correspondences and generate larger inlier<br/><br>
sets with higher probability. We demonstrate in synthetic<br/><br>
experiments that our solvers are fast and numerically stable.<br/><br>
For real images, we show that our solvers can be used<br/><br>
in RANSAC loops to provide good initial solutions.}},
author = {{Kuang, Yubin and Åström, Karl}},
booktitle = {{[Host publication title missing]}},
keywords = {{Computer vision; pose; line; points; quiver; rich feature}},
language = {{eng}},
pages = {{529--536}},
publisher = {{Computer Vision Foundation}},
title = {{Pose Estimation with Unknown Focal Length using Points, Directions and Lines}},
url = {{https://lup.lub.lu.se/search/files/5779526/4249660.pdf}},
year = {{2013}},
}