[1] |
MEHRABIAN A, RUSSELL JA. An Approach to Environmental Psychology[M]. Cambridge: MITPress, 1974.
|
[2] |
EKMAN R. What the face reveals: basic and applied studies of spontaneous expression using the Facial Action Coding System (FACS)[M]. Oxford University Press, USA, 1997.
|
[3] |
EKMAN P, FRIESEN W V. Facial action coding system[J]. Environmental Psychology & Nonverbal Behavior, 1978.
|
[4] |
XIONG X, DE LA TORRE F. Supervised descent method and its applications to face alignment[C]// Proceedings of the IEEE conference on computer vision and pattern recognition, 2013: 532-539.
|
[5] |
ZHU X, RAMANAN D. Face detection, pose estimation, and landmark localization in the wild[C]// 2012 IEEE conference on computer vision and pattern recognition. IEEE, 2012: 2879-2886.
|
[6] |
ASTHANA A, ZAFEIRIOU S, Cheng S, et al. Robust discriminative response map fitting with constrained local models[C]// Proceedings of the IEEE conference on computer vision and pattern recognition, 2013: 3444-3451.
|
[7] |
KING DE. Dlib-ml: A machine learning toolkit[J]. The Journal of Machine Learning Research, 2009, 10: 1755-1758.
|
[8] |
ZHANG K, ZHANG Z, LI Z, et al. Joint face detection and alignment using multitask cascaded convolutional networks[J]. IEEE Signal Processing Letters, 2016, 23(10): 1499-1503.
doi: 10.1109/LSP.2016.2603342
URL
|
[9] |
ALP GULER R, TRIGEORGIS G, ANTONAKOS E, et al. Densereg: fully convolutional dense shape regression in-the-wild[C]// Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017: 6799-6808.
|
[10] |
HU P, RAMANAN D. Finding tiny faces[C]// Proceedings of the IEEE conference on computer vision and pattern recognition, 2017: 951-959.
|
[11] |
SHIN M, KIM M, KWON DS. Baseline CNN structure analysis for facial expression recognition[C]// 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN). IEEE, 2016: 724-729.
|
[12] |
LI J, LAM EY. Facial expression recognition using deep neural networks[C]// 2015 IEEE International Conference on Imaging Systems and Techniques (IST). IEEE, 2015: 1-6.
|
[13] |
EBRAHIMI KAHOU S, MICHALSKI V, KONDA K, et al. Recurrent neural networks for emotion recognition in video[C]// Proceedings of the 2015 ACM on International Conference on Multimodal Interaction, 2015: 467-474.
|
[14] |
BARGAL S A, BARSOUM E, FERRER CC, et al. Emotion recognition in the wild from videos using images[C]// Proceedings of the 18th ACM International Conference on Multimodal Interaction, 2016: 433-436.
|
[15] |
PITALOKA DA, WULANDARI A, BASARUDDIN T, et al. Enhancing CNN with preprocessing stage in automatic emotion recognition[J]. Procedia computer science, 2017, 116: 523-529.
doi: 10.1016/j.procs.2017.10.038
URL
|
[16] |
KUO CM, LAI S H, SARKIS M. A compact deep learning model for robust facial expression recognition[C]// Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018: 2121-2129.
|
[17] |
YIN X, YU X, SOHN K, et al. Towards large-pose face frontalization in the wild[C]// Proceedings of the IEEE international conference on computer vision, 2017: 3990-3999.
|
[18] |
HUANG R, ZHANG S, LI T, et al. Beyond face rotation: Global and local perception gan for photorealistic and identity preserving frontal view synthesis[C]// Proceedings of the IEEE International Conference on Computer Vision, 2017: 2439-2448.
|
[19] |
TRAN L, YIN X, LIU X. Disentangled representation learning gan for pose-invariant face recognition[C]// Proceedings of the IEEE conference on computer vision and pattern recognition, 2017: 1415-1424.
|
[20] |
周书仁, 梁昔明, 朱灿, 等. 基于ICA和HMM 的表情识别[J]. 中国图象图形学报, 2008, 13(12): 2321-2328.
|
[21] |
周书仁. 人脸表情识别算法分析与研究[D]. 长沙: 中南大学, 2009.
|
[22] |
KYPEROUNTAS M, TEFAS A, PITAS I. Salient feature and reliable classifier selection for facial expression classification[J]. Pattern Recognition, 2010, 43(3): 972-986.
doi: 10.1016/j.patcog.2009.07.007
URL
|
[23] |
GU W, XIANG C, VENKATESH YV, et al. Facial expression recognition using radial encoding of local Gabor features and classifier synthesis[J]. Pattern Recognition, 2012, 45(1): 80-91.
doi: 10.1016/j.patcog.2011.05.006
URL
|
[24] |
COHN JF, ZLOCHOWER AJ, LIEN JJ, et al. Feature-point tracking by optical flow discriminates subtle differences in facial expression[C]// Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition. IEEE, 1998: 396-401.
|
[25] |
ANDERSON K, MCOWAN PW. A real-time automated system for the recognition of human facial expressions[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2006, 36(1): 96-105.
doi: 10.1109/TSMCB.2005.854502
URL
|
[26] |
TSALAKANIDOU F, MALASSIOTIS S. Real-time 2D+3D facial action and expression recognition[J]. Pattern Recognition, 2010, 43(5): 1763-1775.
doi: 10.1016/j.patcog.2009.12.009
URL
|
[27] |
HINTON GE, OSINDERO S, Teh YW. A fast learning algorithm for deep belief nets[J]. Neural computation, 2006, 18(7): 1527-1554.
doi: 10.1162/neco.2006.18.7.1527
URL
|
[28] |
LIU P, HAN S, MENG Z, et al. Facial expression recognition via a boosted deep belief network[C]// Proceedings of the IEEE conference on computer vision and pattern recognition. 2014: 1805-1812.
|
[29] |
LIU M, LI S, SHAN S, et al. Au-inspired deep networks for facial expression feature learning[J]. Neurocomputing, 2015, 159: 126-136.
doi: 10.1016/j.neucom.2015.02.011
URL
|
[30] |
HINTON GE, SALAKHUTDINOV RR. Reducing the dimensionality of data with neural networks[J]. Science, 2006, 313(5786): 504-507.
doi: 10.1126/science.1127647
URL
|
[31] |
ZENG N, ZHANG H, SONG B, et al. Facial expression recognition via learning deep sparse autoencoders[J]. Neurocomputing, 2018, 273: 643-649.
doi: 10.1016/j.neucom.2017.08.043
URL
|
[32] |
WU Y, QIU W. Facial expression recognition based on improved local ternary pattern and stacked auto-encoder[C]// AIP Conference Proceedings. AIP Publishing LLC, 2017, 1864(1): 020131.
|
[33] |
SUN B, LI L, ZHOU G, et al. Facial expression recognition in the wild based on multimodal texture features[J]. Journal of Electronic Imaging, 2016, 25(6): 061407.
doi: 10.1117/1.JEI.25.6.061407
URL
|
[34] |
SUN B, LI L, ZHOU G, et al. Combining multimodal features within a fusion network for emotion recognition in the wild[C]// Proceedings of the 2015 ACM on International Conference on Multimodal Interaction, 2015: 497-502.
|
[35] |
GIRSHICK R, DONAHUE J, DARRELL T, et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C]// Proceedings of the IEEE conference on computer vision and pattern recognition, 2014: 580-587.
|
[36] |
CUI R, LIU M, LIU M. Facial expression recognition based on ensemble of mulitple CNNs[C]// Chinese Conference on Biometric Recognition. Springer, Cham, 2016: 511-518.
|
[37] |
孙晓, 潘汀, 任福继. 基于 ROI-KNN 卷积神经网络的面部表情识别[J]. 自动化学报, 2016, 42(6): 883-891.
|
[38] |
WANG X, WANG X, NI Y. Unsupervised domain adaptation for facial expression recognition using generative adversarial networks[J]. Computational Intelligence and Neuroscience, 2018:1-10.
|
[39] |
LAI YH, LAI SH. Emotion-preserving representation learning via generative adversarial network for multi-view facial expression recognition[C]// 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018). IEEE, 2018: 263-270.
|
[40] |
ZHANG F, ZHANG T, MAO Q, et al. Joint pose and expression modeling for facial expression recognition[C]// Proceedings of the IEEE conference on computer vision and pattern recognition, 2018: 3359-3368.
|
[41] |
ZHANG Y, JI Q. Active and dynamic information fusion for facial expression understanding from image sequences[J]. IEEE Transactions on pattern analysis and machine intelligence, 2005, 27(5): 699-714.
doi: 10.1109/TPAMI.2005.93
URL
|
[42] |
WANG TH, LIEN JJJ. Facial expression recognition system based on rigid and non-rigid motion separation and 3D pose estimation[J]. Pattern Recognition, 2009, 42(5): 962-977.
doi: 10.1016/j.patcog.2008.09.035
URL
|
[43] |
徐文晖, 孙正兴. 面向视频序列表情分类的LSVM算法[J]. 计算机辅助设计与图形学学报, 2009, 21(4): 542-548.
|
[44] |
徐琴珍, 章品正, 裴文江, 等. 基于混淆交叉支撑向量机树的自动面部表情分类方法[J]. 中国图象图形学报, 2008, 13(7):1329-1334.
|
[45] |
New handbook of methods in nonverbal behavior research[M]. Oxford University Press, 2008.
|
[46] |
LUCEY P, COHN JF, MATTHEWS I, et al. Automatically detecting pain in video through facial action units[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2010, 41(3): 664-674.
doi: 10.1109/TSMCB.2010.2082525
URL
|
[47] |
DU S, TAO Y, MARTINEZ A M. Compound facial expressions of emotion[J]. Proceedings of the National Academy of Sciences, 2014, 111(15): E1454-E1462.
|
[48] |
LI Y, ZENG J, SHAN S, et al. Occlusion aware facial expression recognition using cnn with attention mechanism[J]. IEEE Transactions on Image Processing, 2018, 28(5): 2439-2450.
doi: 10.1109/TIP.2018.2886767
URL
|
[49] |
HE K, ZHANG X, REN S, et al. Deep residual learning for image recognition[C]// Proceedings of the IEEE conference on computer vision and pattern recognition, 2016: 770-778.
|