Pose Estimation with Unknown Focal Length using Points, Directions and Lines
Författare
Summary, in English
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.
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.
Avdelning/ar
Publiceringsår
2013
Språk
Engelska
Sidor
529-536
Publikation/Tidskrift/Serie
[Host publication title missing]
Fulltext
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Länkar
Dokumenttyp
Konferensbidrag
Förlag
Computer Vision Foundation
Ämne
- Mathematics
Nyckelord
- Computer vision
- pose
- line
- points
- quiver
- rich feature
Conference name
IEEE International Conference on Computer Vision (ICCV), 2013
Conference date
2013-12-01 - 2013-12-08
Conference place
Sydney, Australia
Status
Published
Forskningsgrupp
- Mathematical Imaging Group