4DFAB: A Large Scale 4D Facial Expression Database for Biometric Applications

December 05, 2017 Β· Declared Dead Β· πŸ› Computer Vision and Pattern Recognition

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Authors Shiyang Cheng, Irene Kotsia, Maja Pantic, Stefanos Zafeiriou arXiv ID 1712.01443 Category cs.CV: Computer Vision Citations 17 Venue Computer Vision and Pattern Recognition Last Checked 4 months ago
Abstract
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.
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