Global motion estimation from point matches

Mica Arie-Nachimson, Shahar Z. Kovalsky, Ira Kemelmacher-Shlizerman, Amit Singer, Ronen Basri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

108 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationProceedings - 2nd Joint 3DIM/3DPVT Conference
Subtitle of host publication3D Imaging, Modeling, Processing, Visualization and Transmission, 3DIMPVT 2012
Pages81-88
Number of pages8
DOIs
StatePublished - Dec 1 2012
Event2nd Joint 3DIM/3DPVT Conference: 3D Imaging, Modeling, Processing, Visualization and Transmission, 3DIMPVT 2012 - Zurich, Switzerland
Duration: Oct 13 2012Oct 15 2012

Publication series

NameProceedings - 2nd Joint 3DIM/3DPVT Conference: 3D Imaging, Modeling, Processing, Visualization and Transmission, 3DIMPVT 2012

Other

Other2nd Joint 3DIM/3DPVT Conference: 3D Imaging, Modeling, Processing, Visualization and Transmission, 3DIMPVT 2012
CountrySwitzerland
CityZurich
Period10/13/1210/15/12

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Modeling and Simulation

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