D. Kollias, M. A. Nicolaou, I. Kotsia, G. Zhao and S. Zafeiriou, "Recognition of Affect in the Wild Using Deep Neural Networks," 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Honolulu, HI, 2017, pp. 1972-1979. doi: 10.1109/CVPRW.2017.247
Recognition of affect in the wild using deep neural networks
|Author:||Kollias, Dimitrios1; Nicolaou, Mihalis A.2; Kotsia, Irene3,4;|
1Department of Computing, Imperial College London, UK
2Department of Computing, Goldsmiths, University of London, UK
3School of Science and Technology, International Hellenic University, Greece
4Department of Computer Science, Middlesex University, UK
5Center for Machine Vision and Signal Analysis, University of Oulu, Finland
|Online Access:||PDF Full Text (PDF, 1 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe201902276439
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2019-02-27
In this paper we utilize the first large-scale "in-the-wild" (Aff-Wild) database, which is annotated in terms of the valence-arousal dimensions, to train and test an end-to-end deep neural architecture for the estimation of continuous emotion dimensions based on visual cues. The proposed architecture is based on jointly training convolutional (CNN) and recurrent neural network (RNN) layers, thus exploiting both the invariant properties of convolutional features, while also modelling temporal dynamics that arise in human behaviour via the recurrent layers. Various pre-trained networks are used as starting structures which are subsequently appropriately fine-tuned to the Aff-Wild database. Obtained results show premise for the utilization of deep architectures for the visual analysis of human behaviour in terms of continuous emotion dimensions and analysis of different types of affect.
IEEE Computer Society Conference on Computer Vision and Pattern Recognition workshops
|Pages:||1972 - 1979|
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). Honolulu, Hawaii 21-26 July 2017
IEEE computer society conference on computer vision and pattern recognition workshops
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
113 Computer and information sciences
The work of Stefanos Zafeiriou has been partially funded by the FiDiPro program of Tekes (project number: 1849/31/2015). The work of Dimitris Kollias was funded by a Teaching Fellowship of Imperial College London. We would like also to acknowledge the contribution of the Youtube users that gave us the permission to use their videos (especially Zalzar and Eddie from The1stTake).
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