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

被引:60
作者
Cheng, Shiyang [1 ]
Kotsia, Irene [2 ]
Pantic, Maja [1 ]
Zafeiriou, Stefanos [1 ]
机构
[1] Imperial Coll London, London, England
[2] Middlesex Univ London, London, England
来源
2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) | 2018年
基金
英国工程与自然科学研究理事会;
关键词
3D;
D O I
10.1109/CVPR.2018.00537
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:5117 / 5126
页数:10
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