Combining modality specific deep neural networks for emotion recognition in video

ICMI 2013 - Proceedings of the 2013 ACM International Conference on Multimodal Interaction

Volumn , Issue , 2013, Pages 543-550

  Kahou, Samira Ebrahimi ^a   Pal, Christopher ^a   Bouthillier, Xavier ^b   Froumenty, Pierre ^a   Gülçehre, Çaǧlar ^b   Memisevic, Roland ^b   Vincent, Pascal ^b   Courville, Aaron ^b   Bengio, Yoshua ^b   Ferrari, Raul Chandias ^b   Mirza, Mehdi ^b   Jean, Sébastien ^b   Carrier, Pierre Luc ^b   Dauphin, Yann ^b   Boulanger Lewandowski, Nicolas ^b   Aggarwal, Abhishek ^b   Zumer, Jeremie ^b   Lamblin, Pascal ^b   Raymond, Jean Philippe ^b   Desjardins, Guillaume ^b   Pascanu, Razvan ^b   Warde Farley, David ^b   Torabi, Atousa ^b   Sharma, Arjun ^b   Bengio, Emmanuel ^b   Konda, Kishore Reddy ^c   Wu, Zhenzhou ^d   more..

^a ÉCOLE POLYTECHNIQUE DE MONTRÉAL   (Canada)

^b UNIVERSITÉ DE MONTRÉAL   (Canada)

^c GOETHE UNIVERSITY   (Germany)

^d MCGILL UNIVERSITY   (Canada)

Author keywords

emotion recognition

Indexed keywords

BACKGROUND MUSICS; CONVOLUTIONAL NEURAL NETWORK; DEEP NEURAL NETWORKS; EMOTION RECOGNITION; FACIAL EXPRESSIONS; FRAME AGGREGATION; PERFORMANCE CHARACTERISTICS; SPATIOTEMPORAL INFORMATION;

AUDIO ACOUSTICS; INTERACTIVE COMPUTER SYSTEMS; NETWORK ARCHITECTURE; NEURAL NETWORKS; VIDEO CAMERAS;

SEARCH ENGINES;

EID: 84892582758     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2522848.2531745     Document Type: Conference Paper

References (22)

1. J. Bergstra and Y. Bengio. Random search for hyper-parameter optimization. The Journal of Machine Learning Research, 13:281-305, 2012.
2. P.-L. Carrier, A. Courville, I. J. Goodfellow, M. Mirza, and Y. Bengio. FER-2013 Face Database. Technical report, 1365, Université de Montréal, 2013.
3. C.-C. Chang and C.-J. Lin. LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2:27:1-27:27, 2011. Software available at http://www.csie.ntu.edu.tw/∼cjlin/libsvm.
4. A. Coates, H. Lee, and A. Y. Ng. An Analysis of Single-Layer Networks in Unsupervised Feature Learning. In AISTATS, 2011.
5. G. E. Dahl, T. N. Sainath, and G. E. . Improving deep neural networks for lvcsr using rectified linear units and dropout. In Proc. ICASSP, 2013.
6. A. Dhall, R. Goecke, J. Joshi, M. Wagner, and T. Gedeon. Emotion recognition in the wild challenge 2013. In ACM ICMI, 2013.
7. A. Dhall, R. Goecke, S. Lucey, and T. Gedeon. Collecting large, richly annotated facial-expression databases from movies. IEEE Multimedia, 2012.
8. Google. The Google picasa face detector, 2013. [Online, accessed 1-August-2013].
9. P. Hamel, S. Lemieux, Y. Bengio, and D. Eck. Temporal pooling and multiscale learning for automatic annotation and ranking of music audio. In ISMIR, pages 729-734, 2011.
10. G. Heusch, F. Cardinaux, and S. Marcel. Lighting normalization algorithms for face verification. IDIAP Communication Com05-03, 2005.
11. G. Hinton, L. Deng, D. Yu, G. E. Dahl, A.-r. Mohamed, N. Jaitly, A. Senior, V. Vanhoucke, P. Nguyen, T. N. Sainath, et al. Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups. IEEE Sig. Proc. Magazine, 29(6):82-97, 2012.
12. G. E. Hinton, N. Srivastava, A. Krizhevsky, I. Sutskever, and R. R. Salakhutdinov. Improving neural networks by preventing co-adaptation of feature detectors. arXiv preprint arXiv:1207.0580, 2012.
13. K. R. Konda, R. Memisevic, and V. Michalski. The role of spatio-temporal synchrony in the encoding of motion. arXiv preprint arXiv:1306.3162, 2013.
14. A. Krizhevsky. Cuda-convnet Google code home page. https://code.google. com/p/cuda-convnet/, Aug. 2012.
15. A. Krizhevsky, I. Sutskever, and G. Hinton. Imagenet classification with deep convolutional neural networks. In NIPS, pages 1106-1114. 2012.
16. Q. Le, W. Zou, S. Yeung, and A. Ng. Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis. In CVPR, 2011.
17. V. Štruc and N. Pavešić. Gabor-based kernel partial-least-squares discrimination features for face recognition. Informatica, 20(1):115-138, 2009.
18. J. Susskind, A. Anderson, and G. Hinton. The toronto face database. Technical report, UTML TR 2010-001, University of Toronto, 2010.
19. I. Sutskever, J. Martens, G. Dahl, and G. Hinton. On the importance of initialization and momentum in deep learning. In ICML 2013, 2013.
20. V. Štruc and N. Pavešić. Photometric normalization techniques for illumination invariance, pages 279-300. IGI-Global, 2011.
21. H. Wang, M. M. Ullah, A. Kläser, I. Laptev, and C. Schmid. Evaluation of local spatio-temporal features for action recognition. In BMVC, 2009.
22. X. Zhu and D. Ramanan. Face Detection, Pose Estimation, and Landmark Localization in the Wild. In CVPR, 2012.