Least squares congealing for unsupervised alignment of images

@article{Cox2008LeastSC,
  title={Least squares congealing for unsupervised alignment of images},
  author={Mark Cox and Sridha Sridharan and Simon Lucey and Jeffrey F. Cohn},
  journal={2008 IEEE Conference on Computer Vision and Pattern Recognition},
  year={2008},
  pages={1-8}
}
In this paper, we present an approach we refer to as ldquoleast squares congealingrdquo which provides a solution to the problem of aligning an ensemble of images in an unsupervised manner. Our approach circumvents many of the limitations existing in the canonical ldquocongealingrdquo algorithm. Specifically, we present an algorithm that:- (i) is able to simultaneously, rather than sequentially, estimate warp parameter updates, (ii) exhibits fast convergence and (iii) requires no pre-defined… CONTINUE READING
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