We propose a correlation-based approach to parametric object alignment particularly suitable for face analysis applications which require efficiency and robustness against occlusions and illumination changes. Our algorithm registers two images by iteratively maximising their correlation coefficient using gradient ascent. We compute this correlation coefficient from complex gradients which capture the orientation of image structures rather than pixel intensities. The maximisation of this gradient correlation coefficient results in an algorithm which is as computationally efficient as L2 norm-based algorithms, can be extended within the inverse compositional framework (without the need for Hessian re-computation) and is robust to outliers. To the best of our knowledge, no other algorithm has been proposed so far having all three features.
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Object/Face Alignment Matlab Code: (requires matlab)