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Deep Structure Inference Network for Facial Action Unit Recognition [article]

Ciprian A. Corneanu, Meysam Madadi, Sergio Escalera
2018 arXiv   pre-print
Facial expressions are combinations of basic components called Action Units (AU). Recognizing AUs is key for developing general facial expression analysis.  ...  In recent years, most efforts in automatic AU recognition have been dedicated to learning combinations of local features and to exploiting correlations between Action Units.  ...  Conclusion We proposed the Deep Structured Inference Network (DSIN), a deep network designed to deal with patch and multi-label learning for AU recognition in an integrated way.  ... 
arXiv:1803.05873v2 fatcat:tfpoqwsqarct5hksyzhvuqaxqy

Deep Structure Inference Network for Facial Action Unit Recognition [chapter]

Ciprian Corneanu, Meysam Madadi, Sergio Escalera
2018 Lecture Notes in Computer Science  
Facial expressions are combinations of basic components called Action Units (AU). Recognizing AUs is key for general facial expression analysis.  ...  to a graphical model inference approach in later stages.  ...  We gratefully acknowledge the support of NVIDIA Corporation with the donation of the GPU used for this research.  ... 
doi:10.1007/978-3-030-01258-8_19 fatcat:rhkj5wbpfzd53dde75phjl63ie

Facial Expression Recognition Using Deep Neural Network and Decision Fusion

Xiuyou Wang, Dongqing Xu
2016 Innovative Computing Information and Control Express Letters, Part B: Applications  
Third, the output of the neural network is used for semantic inference, and fuzzy inference system is adopted to implement the high level decision system.  ...  Second, the Local Binary Pattern features are extracted and a deep neural network is trained by Restricted Boltzmann Machine.  ...  Few studies have considered the semantic meanings of facial Action Units (AU).  ... 
doi:10.24507/icicelb.07.09.2055 fatcat:onu3rgosfzefjeno7gp5uaguem

Semantic Relationships Guided Representation Learning for Facial Action Unit Recognition

Guanbin Li, Xin Zhu, Yirui Zeng, Qing Wang, Liang Lin
2019 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Facial action unit (AU) recognition is a crucial task for facial expressions analysis and has attracted extensive attention in the field of artificial intelligence and computer vision.  ...  In this paper, we investigate how to integrate the semantic relationship propagation between AUs in a deep neural network framework to enhance the feature representation of facial regions, and propose  ...  (Corneanu, Madadi, and Escalera 2018) proposed a deep structured inference network (DSIN) for AU recognition which used deep learning to extract image features and structure inference to capture AU relations  ... 
doi:10.1609/aaai.v33i01.33018594 fatcat:2mjolunbfzgttjdz65grxrpmea

Facial Expression Recognition Research Based on Deep Learning [article]

Yongpei Zhu, Hongwei Fan, Kehong Yuan
2019 arXiv   pre-print
expression recognition convolution neural network forms a detector for the specific facial action unit.  ...  Therefore, we have verified that the convolution neural network has formed a detector for the facial Action unit in the training process to realize the expression recognition.  ...  That is, the network structure associated with the feature graph i constitutes a detector for the facial feature unit j.  ... 
arXiv:1904.09737v3 fatcat:wshlfqk4ufhfvogce4ybgplbye

Discovery of facial motions using deep machine perception

Afsaneh Ghasemi, Simon Denman, Sridha Sridharan, Clinton Fookes
2016 2016 IEEE Winter Conference on Applications of Computer Vision (WACV)  
• Can a deep network trained for facial action recognition in one environment be effective in other environments?  ...  In this paper, we propose a method to learn highly discriminative semantic features directly from facial images by using Deep Convolutional Neural Networks (DCNN) for the task of facial action unit detection  ... 
doi:10.1109/wacv.2016.7477448 dblp:conf/wacv/GhasemiDSF16 fatcat:xzf2vkgclzef5lrxzige5qv4rm

Facial Emotion Recognition Through Detection of Facial Action Units and Their Intensity

Rohan Appasaheb Borgalli, Sunil Surve
2022 Scientific Visualization  
Among state-of-the-art methods for FER systems, detection of facial action units (AUs) showed good results.  ...  Our Proposed method achieves an overall accuracy for Action Unit detection using Xceptionnet network for MMI & DISFA are, giving promising results average F1-score is 72% and 74%, respectively.  ...  [35] proposed a deep structural inference network (DSIN). It is based on CNN architecture to extract features of the entire image and patches separately.  ... 
doi:10.26583/sv.14.1.06 fatcat:qttguvfh65htnkj7cuwb4cpei4

A Review on Deep Learning Algorithms for Speech and Facial Emotion Recognition

Charlyn Pushpa Latha, Mohana Priya
2016 APTIKOM Journal on Computer Science and Information Technologies  
Deep Learning technique has obtained remarkable success in the field of face recognition with 97.5% accuracy. Facial Electromyogram (FEMG) signals are used to detect the different emotions of humans.  ...  It is also known as deep structured learning, hierarchical learning or deep machine learning. The term "deep learning" indicates the method used in training multi-layered neural networks.  ...  Short- Term Memory Neural Networks (CNN- BLSTM) i) Learns the dynamic appearance and shape of facial regions for Action Unit detection.  ... 
doi:10.11591/aptikom.j.csit.118 fatcat:gerpzx54qrgrtf3pqnnzgjywim

A Review on Deep Learning Algorithms for Speech and Facial Emotion Recognition

Charlyn Pushpa Latha, Mohana Priya
2020 APTIKOM Journal on Computer Science and Information Technologies  
It is also known as deep structured learning,hierarchical learning or deep machine learning. The term "deep learning" indicates the method used in trainingmulti-layered neural networks.  ...  Some of the deep learning techniques discussed in this paper are Deep Boltzmann Machine (DBM), DeepBelief Networks (DBN), Convolutional Neural Networks (CNN) and Stacked Auto Encoders respectively.  ...  Short- Term Memory Neural Networks (CNN- BLSTM) i) Learns the dynamic appearance and shape of facial regions for Action Unit detection.  ... 
doi:10.34306/csit.v1i3.55 fatcat:l2tska7j5ferna4wupt3f2jcp4

Semantic Relationships Guided Representation Learning for Facial Action Unit Recognition [article]

Guanbin Li, Xin Zhu, Yirui Zeng, Qing Wang, Liang Lin
2019 arXiv   pre-print
Facial action unit (AU) recognition is a crucial task for facial expressions analysis and has attracted extensive attention in the field of artificial intelligence and computer vision.  ...  In this paper, we investigate how to integrate the semantic relationship propagation between AUs in a deep neural network framework to enhance the feature representation of facial regions, and propose  ...  (Corneanu, Madadi, and Escalera 2018) proposed a deep structured inference network (DSIN) for AU recognition which used deep learning to extract image features and structure inference to capture AU relations  ... 
arXiv:1904.09939v1 fatcat:n7r7pkkspne57bfue52v6ik2nm

Causal Intervention for Subject-Deconfounded Facial Action Unit Recognition [article]

Yingjie Chen, Diqi Chen, Tao Wang, Yizhou Wang, Yun Liang
2022 arXiv   pre-print
In this paper, we propose a causal inference framework for subject-invariant facial action unit recognition.  ...  Subject-invariant facial action unit (AU) recognition remains challenging for the reason that the data distribution varies among subjects.  ...  Our main contributions are listed as: Related Work Facial Action Recognition In recent years, research on facial action unit recognition has seen great achievements.  ... 
arXiv:2204.07935v1 fatcat:mi4ueuluczautjjjzolazo2tv4

Causal affect prediction model using a facial image sequence [article]

Geesung Oh, Euiseok Jeong, Sejoon Lim
2021 arXiv   pre-print
Among human affective behavior research, facial expression recognition research is improving in performance along with the development of deep learning.  ...  In this paper, we propose the causal affect prediction network (CAPNet), which uses only past facial images to predict corresponding affective valence and arousal.  ...  emotions), and 12 facial action unit detection.  ... 
arXiv:2107.03886v1 fatcat:5xk6g2t4cvdsdiicnjaoeh3xoa

Capturing Global Semantic Relationships for Facial Action Unit Recognition

Ziheng Wang, Yongqiang Li, Shangfei Wang, Qiang Ji
2013 2013 IEEE International Conference on Computer Vision  
In this paper we tackle the problem of facial action unit (AU) recognition by exploiting the complex semantic relationships among AUs, which carry crucial top-down information yet have not been thoroughly  ...  Efficient learning and inference algorithms of the proposed model are also developed.  ...  Figure 3 : 3 Proposed hierarchical model for joint facial action units recognition. Left: graphical depiction of the model.  ... 
doi:10.1109/iccv.2013.410 dblp:conf/iccv/WangLWJ13 fatcat:zgzol76gy5balc5onhqr74ubbi

Deep Structured Learning for Facial Action Unit Intensity Estimation

Robert Walecki, Ognjen Rudovic, Vladimir Pavlovic, Bjoern Schuller, Maja Pantic
2017 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
We consider the task of automated estimation of facial expression intensity. This involves estimation of multiple output variables (facial action units -AUs) that are structurally dependent.  ...  We show that joint learning of the deep features and the target output structure results in significant performance gains compared to existing deep structured models for analysis of facial expressions.  ...  FACS defines a unique set of 30+ atomic non-overlapping facial muscle actions named Action Units (AUs) [27] , with rules for scoring their intensity on a six-point ordinal scale.  ... 
doi:10.1109/cvpr.2017.605 dblp:conf/cvpr/WaleckiRPSP17 fatcat:e66unqqze5dghkaj76tbdifohe

Prior Aided Streaming Network for Multi-task Affective Recognitionat the 2nd ABAW2 Competition [article]

Wei Zhang, Zunhu Guo, Keyu Chen, Lincheng Li, Zhimeng Zhang, Yu Ding
2021 arXiv   pre-print
In dealing with different emotion representations, including Categorical Emotions (CE), Action Units (AU), and Valence Arousal (VA), we propose a multi-task streaming network by a heuristic that the three  ...  With recent development of deep learning techniques and large scale in-the-wild annotated datasets, the facial emotion analysis is now aimed at challenges in the real world settings.  ...  One of the evidence is that the similar facial muscle movements (action units) mostly indicate the similar inner statements, and so the perceived facial emotions.  ... 
arXiv:2107.03708v1 fatcat:flg4nwidu5h27mi7zm22fydheq
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