Fetching the paper…
Reading the bibliography…
The integration of information across multiple modalities and across time is a promising way to enhance the emotion recognition performance of affective systems.
P. Ekman and W. V. Friesen, “Constants across cultures in the face and emotion.,” Journal of personality and social psychology
1971
Earlier work this paper cites.
Consulting Psychologists Press, 1978
P. Ekman and W. V. Friesen, Facial Action Coding System: Investigatoris Guide · 1978
Earlier work this paper cites.
T. Wilson, J. Wiebe, and P. Hoffmann, “Recognizing contextual polarity in phrase-level sentiment analysis,” in Proceedings of the conference on human language technology and empirical methods in natural language processing
2005
Earlier work this paper cites.
X. Ding, B. Liu, and P. S. Yu, “A holistic lexicon-based approach to opinion mining,” in Proceedings of the 2008 international conference on web search and data mining
2008
Earlier work this paper cites.
C. Shan, S. Gong, and P. W. McOwan, “Facial expression recognition based on local binary patterns: A comprehensive study,” Image and Vision Computing
2009
Earlier work this paper cites.
L. Kessous, G. Castellano, and G. Caridakis, “Multimodal emotion recognition in speech-based interaction using facial expression, body gesture and acoustic analysis,” Journal on Multimodal User Interfaces
2010
Earlier work this paper cites.
F. Eyben, M. Wöllmer, and B. Schuller, “Opensmile: the munich versatile and fast open-source audio feature extractor,” in Proceedings of the 18th ACM international conference on Multimedia
2010
Earlier work this paper cites.
B. Schuller, S. Steidl, A. Batliner, F. Burkhardt, L. Devillers, C. Müller, and S. Narayanan, “The interspeech 2010 paralinguistic challenge,” in Proc. INTERSPEECH 2010, Makuhari, Japan
2010
Earlier work this paper cites.
R. A. Thompson, “Methods and measures in developmental emotions research: Some assembly required,” Journal of Experimental Child Psychology
2011
Earlier work this paper cites.
L.-P. Morency, R. Mihalcea, and P. Doshi, “Towards multimodal sentiment analysis: Harvesting opinions from the web,” in Proceedings of the 13th international conference on multimodal interfaces
2011
Earlier work this paper cites.
M. Soleymani, M. Pantic, and T. Pun, “Multimodal emotion recognition in response to videos,” IEEE transactions on affective computing
2012
Cited alongside, same era.
T. Baltrušaitis, P. Robinson, and L.-P. Morency, “3d constrained local model for rigid and non-rigid facial tracking,” in Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on
2012
Cited alongside, same era.
V. P. Rosas, R. Mihalcea, and L.-P. Morency, “Multimodal sentiment analysis of spanish online videos,” IEEE Intelligent Systems
2013
Cited alongside, same era.
M. Glodek, S. Reuter, M. Schels, K. Dietmayer, and F. Schwenker, “Kalman filter based classifier fusion for affective state recognition,” in International Workshop on Multiple Classifier Systems
2013
Cited alongside, same era.
J. Pennington, R. Socher, and C. Manning, “Glove: Global vectors for word representation,” in Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP)
S. Poria, E. Cambria, N. Howard, G.-B. Huang, and A. Hussain, “Fusing audio, visual and textual clues for sentiment analysis from multimodal content,” Neurocomputing
2016
Later among the works it cites.
H. Ranganathan, S. Chakraborty, and S. Panchanathan, “Multimodal emotion recognition using deep learning architectures,” in Applications of Computer Vision (WACV), 2016 IEEE Winter Conference on
2016
Later among the works it cites.
T. Baltrušaitis, P. Robinson, and L.-P. Morency, “Openface: an open source facial behavior analysis toolkit,” in Applications of Computer Vision (WACV), 2016 IEEE Winter Conference on
2016
Later among the works it cites.
Y. Zhou and B. E. Shi, “Action unit selective feature maps in deep networks for facial expression recognition,” in Neural Networks (IJCNN), 2017 International Joint Conference on
2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2014
Cited alongside, same era.
P. Khorrami, T. Paine, and T. Huang, “Do deep neural networks learn facial action units when doing expression recognition?,” in Proceedings of the IEEE International Conference on Computer Vision Workshops
2015
Cited alongside, same era.
S. Poria, E. Cambria, A. Hussain, and G.-B. Huang, “Towards an intelligent framework for multimodal affective data analysis,” Neural Networks
2015
Cited alongside, same era.
G. Cai and B. Xia, “Convolutional neural networks for multimedia sentiment analysis,” in Natural Language Processing and Chinese Computing
2015
Cited alongside, same era.
S. Poria, E. Cambria, and A. Gelbukh, “Deep convolutional neural network textual features and multiple kernel learning for utterance-level multimodal sentiment analysis,” in Proceedings of the 2015 conference on empirical methods in natural language processing
2015
Cited alongside, same era.
O. M. Parkhi, A. Vedaldi, A. Zisserman, et al
2015
Cited alongside, same era.
Y. Zhou, J. Pi, and B. E. Shi, “Pose-independent facial action unit intensity regression based on multi-task deep transfer learning,” in Automatic Face & Gesture Recognition (FG 2017), 2017 12th IEEE International Conference on
2017
Later among the works it cites.
P. Tzirakis, G. Trigeorgis, M. A. Nicolaou, B. W. Schuller, and S. Zafeiriou, “End-to-end multimodal emotion recognition using deep neural networks,” IEEE Journal of Selected Topics in Signal Processing
2017
Later among the works it cites.
2017
Later among the works it cites.
2018
Closest in time.
Accessed: 2018-4-30
“Openface output format.” https://github.com/TadasBaltrusaitis/OpenFace/wiki/Output-Format · 2018
Closest in time.
Accessed: 2018-4-30
“opensmile emobase2010 features.” https://github.com/naxingyu/opensmile/blob/master/config/emobase2010.conf · 2018
Closest in time.