4DFAB: a large scale 4D facial expression database for biometric applications

Cheng, Shiyang, Kotsia, Irene ORCID logoORCID: https://orcid.org/0000-0002-3716-010X, Pantic, Maja and Zafeiriou, Stefanos (2018) 4DFAB: a large scale 4D facial expression database for biometric applications. 2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). In: CVPR 2018: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 18-22 June 2018, Salt Lake City, USA. ISBN 9781538664209. [Conference or Workshop Item] (Published online first)

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The progress we are currently witnessing in many computer vision applications, including automatic face analysis, would not be made possible without tremendous efforts in collecting and annotating large scale visual databases. To this end, we propose 4DFAB, a new large scale database of dynamic high-resolution 3D faces (over 1,800,000 3D meshes). 4DFAB contains recordings of 180 subjects captured in four different sessions spanning over a five-year period. It contains 4D videos of subjects displaying both spontaneous and posed facial behaviours. The database can be used for both face and facial expression recognition, as well as behavioural biometrics. It can also be used to learn very powerful blendshapes for parametrising facial behaviour. In this paper, we conduct several experiments and demonstrate the usefulness of the database for various applications. The database will be made publicly available for research purposes.

Item Type: Conference or Workshop Item (Paper)
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 24259
Notes on copyright: © 2018 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: Irene Kotsia
Date Deposited: 14 May 2018 11:48
Last Modified: 29 Nov 2022 19:50
URI: https://eprints.mdx.ac.uk/id/eprint/24259

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