Title
Global Motion Estimation from Point Matches
Abstract
Multiview structure recovery from a collection of images requires the recovery of the positions and orientations of the cameras relative to a global coordinate system. Our approach recovers camera motion as a sequence of two global optimizations. First, pair wise Essential Matrices are used to recover the global rotations by applying robust optimization using either spectral or semi definite programming relaxations. Then, we directly employ feature correspondences across images to recover the global translation vectors using a linear algorithm based on a novel decomposition of the Essential Matrix. Our method is efficient and, as demonstrated in our experiments, achieves highly accurate results on collections of real images for which ground truth measurements are available.
Year
DOI
Venue
2012
10.1109/3DIMPVT.2012.46
3DIMPVT
Keywords
Field
DocType
global motion estimation,approach recovers camera motion,multiview structure recovery,point matches,essential matrix,global rotation,feature correspondence,wise essential matrices,accurate result,global translation,global optimizations,ground truth measurement,structure from motion,3d reconstruction,motion estimation,mathematical programming
Structure from motion,Computer vision,Essential matrix,Matrix (mathematics),Robust optimization,Ground truth,Artificial intelligence,Real image,Motion estimation,Mathematics,Semidefinite programming
Conference
ISBN
Citations 
PageRank 
978-1-4673-4470-8
47
1.31
References 
Authors
17
6
Name
Order
Citations
PageRank
Mica Arie-Nachimson1471.31
Shahar Z. Kovalsky219210.87
Ira Kemelmacher-Shlizerman371028.03
A. Singer469552.77
Ronen Basri53467403.18
Arie-Nachimson, M.6471.31