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IJCV
2012

Globally Optimal Estimation of Nonrigid Image Distortion

8 years 2 months ago
Globally Optimal Estimation of Nonrigid Image Distortion
Abstract Image alignment in the presence of non-rigid distortions is a challenging task. Typically, this involves estimating the parameters of a dense deformation field that warps a distorted image back to its undistorted template. Generative approaches based on parameter optimization such as Lucas-Kanade can get trapped within local minima. On the other hand, discriminative approaches like nearestneighbor require a large number of training samples that grows exponentially with respect to the dimension of the parameter space, and polynomially with the desired accuracy 1/ . In this work, we develop a novel data-driven iterative algorithm that combines the best of both generative and discriminative approaches. For this, we introduce the notion of a “pull-back” operation that enables us to predict the parameters of the test image using training samples that are not in its neighborhood (not -close) in the parameter space. We prove that our algorithm converges to the global optimum usi...
Yuandong Tian, Srinivasa G. Narasimhan
Added 29 Sep 2012
Updated 29 Sep 2012
Type Journal
Year 2012
Where IJCV
Authors Yuandong Tian, Srinivasa G. Narasimhan
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