Recovery of Epipolar Geometry as a Manifold Fitting Problem

I
ICCV
2003
Ninth IEEE International Conference on Computer Vision (ICCV'03) - Volume 2
Abstract - Recovery of Epipolar Geometry as a Manifold Fitting Problem

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Ninth IEEE International Conference on Computer Vision (ICCV'03) - Volume 2

Nice, France

October 13-October 16

ISBN: 0-7695-1950-4

	ASCII Text	x
	Liran Goshen, Ilan Shimshoni, P. Anandan, Daniel Keren, "Recovery of Epipolar Geometry as a Manifold Fitting Problem," Computer Vision, IEEE International Conference on, vol. 2, pp. 1321, Ninth IEEE International Conference on Computer Vision (ICCV'03) - Volume 2, 2003.

	BibTex	x
	@article{ 10.1109/ICCV.2003.1238643, author = {Liran Goshen and Ilan Shimshoni and P. Anandan and Daniel Keren}, title = {Recovery of Epipolar Geometry as a Manifold Fitting Problem}, journal ={Computer Vision, IEEE International Conference on}, volume = {2}, year = {2003}, isbn = {0-7695-1950-4}, pages = {1321}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICCV.2003.1238643}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computer Vision, IEEE International Conference on TI - Recovery of Epipolar Geometry as a Manifold Fitting Problem SN - 0-7695-1950-4 SP EP A1 - Liran Goshen, A1 - Ilan Shimshoni, A1 - P. Anandan, A1 - Daniel Keren, PY - 2003 KW - null VL - 2 JA - Computer Vision, IEEE International Conference on ER -

Liran Goshen, Technion

Ilan Shimshoni, Technion

P. Anandan, Microsoft Research

Daniel Keren, Haifa University

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICCV.2003.1238643

The introduction of the joint image manifold allows to treat the problem of recovering camera motion and epipolar geometry as the problem of fitting a manifold to the data measured in a stereo pair. The manifold has a singularity and boundary, therefore care must be taken when fitting it.

This paper reviews the notion of joint image manifold, and how previous motion recovery methods can be viewed in its context, and then offers a new fitting method, which improves upon previous results, especially when the extent of the data and/or the motion are small.

Citation:

Liran Goshen, Ilan Shimshoni, P. Anandan, Daniel Keren, "Recovery of Epipolar Geometry as a Manifold Fitting Problem," iccv, vol. 2, pp.1321, Ninth IEEE International Conference on Computer Vision (ICCV'03) - Volume 2, 2003

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