Learning Affective Features With a Hybrid Deep Model for Audio–Visual Emotion Recognition
暂无分享,去创建一个
Wen Gao | Qi Tian | Tiejun Huang | Shiqing Zhang | Shiliang Zhang | Q. Tian | Tiejun Huang | Shiliang Zhang | Shiqing Zhang | Wen Gao
[1] Shiqing Zhang,et al. A Review on Facial Expression Recognition: Feature Extraction and Classification , 2016 .
[2] Jiri Matas,et al. On Combining Classifiers , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[3] Gerald Penn,et al. Convolutional Neural Networks for Speech Recognition , 2014, IEEE/ACM Transactions on Audio, Speech, and Language Processing.
[4] Yuming Zhou,et al. A novel ensemble method for classifying imbalanced data , 2015, Pattern Recognit..
[5] Nicholas B. Allen,et al. Stress and emotion recognition using log-Gabor filter analysis of speech spectrograms , 2009, 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops.
[6] Björn W. Schuller,et al. Context-Sensitive Learning for Enhanced Audiovisual Emotion Classification , 2012, IEEE Transactions on Affective Computing.
[7] Chung-Hsien Wu,et al. Error Weighted Semi-Coupled Hidden Markov Model for Audio-Visual Emotion Recognition , 2012, IEEE Transactions on Multimedia.
[8] Björn W. Schuller,et al. Audiovisual recognition of spontaneous interest within conversations , 2007, ICMI '07.
[9] Reza Boostani,et al. FF-SKPCCA: Kernel probabilistic canonical correlation analysis , 2017, Applied Intelligence.
[10] Yifeng He,et al. Multiview emotion recognition via multi-set locality preserving canonical correlation analysis , 2016, 2016 IEEE International Symposium on Circuits and Systems (ISCAS).
[11] Chong-Wah Ngo,et al. Mutlimodal Learning with Deep Boltzmann Machine for Emotion Prediction in User Generated Videos , 2015, ICMR.
[12] Paul A. Viola,et al. Robust Real-Time Face Detection , 2001, International Journal of Computer Vision.
[13] Chun Chen,et al. A robust multimodal approach for emotion recognition , 2008, Neurocomputing.
[14] Emily Mower Provost,et al. Identifying salient sub-utterance emotion dynamics using flexible units and estimates of affective flow , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[15] Markus Kächele,et al. Multiple Classifier Systems for the Classification of Audio-Visual Emotional States , 2011, ACII.
[16] Juhan Nam,et al. Multimodal Deep Learning , 2011, ICML.
[17] Chong-Wah Ngo,et al. Deep Multimodal Learning for Affective Analysis and Retrieval , 2015, IEEE Transactions on Multimedia.
[18] Shiqing Zhang,et al. Facial expression recognition using local binary patterns and discriminant kernel locally linear embedding , 2012, EURASIP Journal on Advances in Signal Processing.
[19] Matti Pietikäinen,et al. Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[20] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[21] Andrew Zisserman,et al. Reading Text in the Wild with Convolutional Neural Networks , 2014, International Journal of Computer Vision.
[22] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[23] Zhengyou Zhang,et al. Comparison between geometry-based and Gabor-wavelets-based facial expression recognition using multi-layer perceptron , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.
[24] Honglak Lee,et al. Deep learning for robust feature generation in audiovisual emotion recognition , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[25] Thierry Pun,et al. Multimodal Emotion Recognition in Response to Videos , 2012, IEEE Transactions on Affective Computing.
[26] Björn W. Schuller,et al. LSTM-Modeling of continuous emotions in an audiovisual affect recognition framework , 2013, Image Vis. Comput..
[27] Geoffrey E. Hinton,et al. A Better Way to Pretrain Deep Boltzmann Machines , 2012, NIPS.
[28] Zhihong Zeng,et al. A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[29] Bingbing Ni,et al. Person Re-identification via Recurrent Feature Aggregation , 2016, ECCV.
[30] M. Shamim Hossain,et al. Audio–Visual Emotion-Aware Cloud Gaming Framework , 2015, IEEE Transactions on Circuits and Systems for Video Technology.
[31] A. Hanjalic,et al. Extracting moods from pictures and sounds: towards truly personalized TV , 2006, IEEE Signal Processing Magazine.
[32] Erik Cambria,et al. Ensemble application of convolutional neural networks and multiple kernel learning for multimodal sentiment analysis , 2017, Neurocomputing.
[33] Björn W. Schuller,et al. AVEC 2013: the continuous audio/visual emotion and depression recognition challenge , 2013, AVEC@ACM Multimedia.
[34] Johannes Wagner,et al. Exploring Fusion Methods for Multimodal Emotion Recognition with Missing Data , 2011, IEEE Transactions on Affective Computing.
[35] Ling Guan,et al. Multimodal Information Fusion of Audio Emotion Recognition Based on Kernel Entropy Component Analysis , 2013, Int. J. Semantic Comput..
[36] Lei Gao,et al. Information fusion based on kernel entropy component analysis in discriminative canonical correlation space with application to audio emotion recognition , 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[37] Tamás D. Gedeon,et al. Video and Image based Emotion Recognition Challenges in the Wild: EmotiW 2015 , 2015, ICMI.
[38] Cécile Barat,et al. String representations and distances in deep Convolutional Neural Networks for image classification , 2016, Pattern Recognit..
[39] Tamás D. Gedeon,et al. Emotion recognition using PHOG and LPQ features , 2011, Face and Gesture 2011.
[40] Qi Tian,et al. MARS: A Video Benchmark for Large-Scale Person Re-Identification , 2016, ECCV.
[41] Yifeng He,et al. Multiview learning via deep discriminative canonical correlation analysis , 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[42] Geoffrey E. Hinton,et al. Reducing the Dimensionality of Data with Neural Networks , 2006, Science.
[43] Geoffrey E. Hinton. Training Products of Experts by Minimizing Contrastive Divergence , 2002, Neural Computation.
[44] Ling Guan,et al. Kernel Cross-Modal Factor Analysis for Information Fusion With Application to Bimodal Emotion Recognition , 2012, IEEE Transactions on Multimedia.
[45] Björn W. Schuller,et al. The INTERSPEECH 2010 paralinguistic challenge , 2010, INTERSPEECH.
[46] Maja Pantic,et al. Facial Expression Recognition , 2009, Encyclopedia of Biometrics.
[47] Yixin Chen,et al. Compressing Neural Networks with the Hashing Trick , 2015, ICML.
[48] Cigdem Eroglu Erdem,et al. BAUM-1: A Spontaneous Audio-Visual Face Database of Affective and Mental States , 2017, IEEE Transactions on Affective Computing.
[49] Björn W. Schuller,et al. Acoustic emotion recognition: A benchmark comparison of performances , 2009, 2009 IEEE Workshop on Automatic Speech Recognition & Understanding.
[50] Shaogang Gong,et al. Facial expression recognition based on Local Binary Patterns: A comprehensive study , 2009, Image Vis. Comput..
[51] Carlos Busso,et al. Using neutral speech models for emotional speech analysis , 2007, INTERSPEECH.
[52] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[53] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[54] Zhihong Zeng,et al. Audio–Visual Affective Expression Recognition Through Multistream Fused HMM , 2008, IEEE Transactions on Multimedia.
[55] Xiaogang Wang,et al. DeepID-Net: Deformable deep convolutional neural networks for object detection , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[56] Lorenzo Torresani,et al. Learning Spatiotemporal Features with 3D Convolutional Networks , 2014, 2015 IEEE International Conference on Computer Vision (ICCV).
[57] Haizhou Li,et al. Audio and face video emotion recognition in the wild using deep neural networks and small datasets , 2016, ICMI.
[58] Alex Acero,et al. Spoken Language Processing: A Guide to Theory, Algorithm and System Development , 2001 .
[59] Zhigang Deng,et al. Analysis of emotion recognition using facial expressions, speech and multimodal information , 2004, ICMI '04.
[60] Nasrollah Moghaddam Charkari,et al. Audiovisual emotion recognition using ANOVA feature selection method and multi-classifier neural networks , 2014, Neural Computing and Applications.
[61] Fakhri Karray,et al. Survey on speech emotion recognition: Features, classification schemes, and databases , 2011, Pattern Recognit..
[62] Tanaya Guha,et al. Multimodal Prediction of Affective Dimensions and Depression in Human-Computer Interactions , 2014, AVEC '14.
[63] Mansour Sheikhan,et al. Audio-visual emotion recognition using FCBF feature selection method and particle swarm optimization for fuzzy ARTMAP neural networks , 2015, Multimedia Tools and Applications.
[64] Shiliang Zhang,et al. Multimodal Deep Convolutional Neural Network for Audio-Visual Emotion Recognition , 2016, ICMR.
[65] Nasrollah Moghaddam Charkari,et al. Multimodal information fusion application to human emotion recognition from face and speech , 2010, Multimedia Tools and Applications.
[66] Ling Guan,et al. Recognizing Human Emotional State From Audiovisual Signals , 2008, IEEE Transactions on Multimedia.
[67] Deepak Khosla,et al. Spiking Deep Convolutional Neural Networks for Energy-Efficient Object Recognition , 2014, International Journal of Computer Vision.