Essential Matrix Estimation Using Gauss-Newton Iterations on a Manifold
A novel approach for essential matrix estimation is presented, this being a key task in stereo vision processing. We estimate the essential matrix from point correspondences between a stereo image pair, assuming that the internal camera parameters are known. The set of essential matrices forms a smooth manifold, and a suitable cost function can be defined on this manifold such that its minimum is the desired essential matrix. We seek a computationally efficient optimization scheme towards...[Show more]
|Collections||ANU Research Publications|
|Source:||International Journal of Computer Vision|
|01_Helmke_Essential_Matrix_Estimation_2007.pdf||682.97 kB||Adobe PDF||Request a copy|
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