Face flow

Snape, Patrick, Roussos, Anastasios, Panagakis, Yannis ORCID logoORCID: https://orcid.org/0000-0003-0153-5210 and Zafeiriou, Stefanos (2015) Face flow. 2015 IEEE International Conference on Computer Vision (ICCV). In: 2015 IEEE International Conference on Computer Vision (ICCV), 07-13 Dec 2015, Santiago, Chile. ISBN 9781467383912. ISSN 2380-7504 [Conference or Workshop Item] (doi:10.1109/ICCV.2015.343)

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In this paper, we propose a method for the robust and efficient computation of multi-frame optical flow in an expressive sequence of facial images. We formulate a novel energy minimisation problem for establishing dense correspondences between a neutral template and every frame of a sequence. We exploit the highly correlated nature of human expressions by representing dense facial motion using a deformation basis. Furthermore, we exploit the even higher correlation between deformations in a given input sequence by imposing a low-rank prior on the coefficients of the deformation basis, yielding temporally consistent optical flow. Our proposed model-based formulation, in conjunction with the inverse compositional strategy and low-rank matrix optimisation that we adopt, leads to a highly efficient algorithm for calculating facial flow. As experimental evaluation, we show quantitative experiments on a challenging novel benchmark of face sequences, with dense ground truth optical flow provided by motion capture data. We also provide qualitative results on a real sequence displaying fast motion and occlusions. Extensive quantitative and qualitative comparisons demonstrate that the proposed method outperforms state-of-the-art optical flow and dense non-rigid registration techniques, whilst running an order of magnitude faster.

Item Type: Conference or Workshop Item (Paper)
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 23777
Notes on copyright: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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Depositing User: Yannis Panagakis
Date Deposited: 06 Mar 2018 18:56
Last Modified: 29 Nov 2022 22:19
URI: https://eprints.mdx.ac.uk/id/eprint/23777

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