Geometry of single axis motions using conic fitting

Previous algorithms for recovering 3D geometry from an uncalibrated image sequence of a single axis motion of unknown rotation angles are mainly based on the computation of two-view fundamental matrices and three-view trifocal tensors. We propose three new methods that are based on fitting a conic l...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on pattern analysis and machine intelligence 2003-10, Vol.25 (10), p.1343-1348
Main Authors: Guang Jiang, Hung-tat Tsui, Long Quan, Zisserman, A.
Format: Article
Language:English
Subjects:
Cameras
Computation
Computational geometry
Conics
Fittings
Image reconstruction
Image sequences
Loci
Mathematical analysis
Mathematics
Maximum likelihood detection
Maximum likelihood estimation
Motion estimation
Robustness
Solid modeling
Tensile stress
Tensors
Three dimensional
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Previous algorithms for recovering 3D geometry from an uncalibrated image sequence of a single axis motion of unknown rotation angles are mainly based on the computation of two-view fundamental matrices and three-view trifocal tensors. We propose three new methods that are based on fitting a conic locus to corresponding image points over multiple views. The main advantage is that determining only five parameters of a conic from one corresponding point over at least five views is simpler and more robust than determining a fundamental matrix from two views or a trifocal tensor from three views. It is shown that the geometry of single axis motion can be recovered either by computing one conic locus and one fundamental matrix or by computing at least two conic loci. A maximum likelihood solution based on this parametrization of the single axis motion is also described for optimal estimation using three or more loci. The experiments on real image sequences demonstrate the simplicity, accuracy, and robustness of the new methods.
ISSN:0162-8828
1939-3539
DOI:10.1109/TPAMI.2003.1233910