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Facial Expression Recognition via Joint Deep Learning of RGB-Depth Map Latent Representations
Oyedotun, Oyebade; Demisse, Girum; Shabayek, Abd El Rahman et al.
2017In 2017 IEEE International Conference on Computer Vision Workshop (ICCVW)
Peer reviewed
 

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Keywords :
Facial expression; recognition; deep learning
Abstract :
[en] Humans use facial expressions successfully for conveying their emotional states. However, replicating such success in the human-computer interaction domain is an active research problem. In this paper, we propose deep convolutional neural network (DCNN) for joint learning of robust facial expression features from fused RGB and depth map latent representations. We posit that learning jointly from both modalities result in a more robust classifier for facial expression recognition (FER) as opposed to learning from either of the modalities independently. Particularly, we construct a learning pipeline that allows us to learn several hierarchical levels of feature representations and then perform the fusion of RGB and depth map latent representations for joint learning of facial expressions. Our experimental results on the BU-3DFE dataset validate the proposed fusion approach, as a model learned from the joint modalities outperforms models learned from either of the modalities.
Research center :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > SIGCOM
Disciplines :
Computer science
Author, co-author :
Oyedotun, Oyebade ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Demisse, Girum ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Shabayek, Abd El Rahman ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Aouada, Djamila  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Ottersten, Björn ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
External co-authors :
yes
Language :
English
Title :
Facial Expression Recognition via Joint Deep Learning of RGB-Depth Map Latent Representations
Publication date :
21 August 2017
Event name :
2017 IEEE International Conference on Computer Vision Workshop (ICCVW)
Event place :
Venice, Italy
Event date :
October 22-29, 2017
Audience :
International
Main work title :
2017 IEEE International Conference on Computer Vision Workshop (ICCVW)
Peer reviewed :
Peer reviewed
Focus Area :
Security, Reliability and Trust
FnR Project :
FNR11295431 - Automatic Feature Selection For Visual Recognition, 2016 (01/02/2017-31/01/2021) - Oyebade Oyedotun
Funders :
This work was funded by the National Research Fund (FNR), Luxembourg, under the project reference R-AGR- 0424-05-D/Bjorn Ottersten
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since 05 September 2017

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