Robust and efficient parametric face alignment

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 maximizing their correlation coefficient...

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Main Authors: Tzimiropoulos, Georgios, Zafeiriou, Stefanos, Pantic, Maja
Format: Conference or Workshop Item
Published: 2011
Online Access:https://eprints.nottingham.ac.uk/31462/
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author Tzimiropoulos, Georgios
Zafeiriou, Stefanos
Pantic, Maja
author_facet Tzimiropoulos, Georgios
Zafeiriou, Stefanos
Pantic, Maja
author_sort Tzimiropoulos, Georgios
building Nottingham Research Data Repository
collection Online Access
description 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 maximizing 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 maximization 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 recomputation) and is robust to outliers. To the best of our knowledge, no other algorithm has been proposed so far having all three features. We show the robustness of our algorithm for the problem of face alignment in the presence of occlusions and non-uniform illumination changes. The code that reproduces the results of our paper can be found at http://ibug.doc.ic.ac.uk/resources.
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format Conference or Workshop Item
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institution University of Nottingham Malaysia Campus
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publishDate 2011
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spelling nottingham-314622020-05-04T20:24:38Z https://eprints.nottingham.ac.uk/31462/ Robust and efficient parametric face alignment Tzimiropoulos, Georgios Zafeiriou, Stefanos Pantic, Maja 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 maximizing 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 maximization 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 recomputation) and is robust to outliers. To the best of our knowledge, no other algorithm has been proposed so far having all three features. We show the robustness of our algorithm for the problem of face alignment in the presence of occlusions and non-uniform illumination changes. The code that reproduces the results of our paper can be found at http://ibug.doc.ic.ac.uk/resources. 2011 Conference or Workshop Item PeerReviewed Tzimiropoulos, Georgios, Zafeiriou, Stefanos and Pantic, Maja (2011) Robust and efficient parametric face alignment. In: 2011 IEEE International Conference on Computer Vision (ICCV), 6-13 November 2011, Barcelona, Spain. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6126452&filter=AND%28p_Publication_Number:6118259%29
spellingShingle Tzimiropoulos, Georgios
Zafeiriou, Stefanos
Pantic, Maja
Robust and efficient parametric face alignment
title Robust and efficient parametric face alignment
title_full Robust and efficient parametric face alignment
title_fullStr Robust and efficient parametric face alignment
title_full_unstemmed Robust and efficient parametric face alignment
title_short Robust and efficient parametric face alignment
title_sort robust and efficient parametric face alignment
url https://eprints.nottingham.ac.uk/31462/
https://eprints.nottingham.ac.uk/31462/