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Human Centered Interfaces for Assisted Living
[chapter]
2011
Advances in Intelligent and Soft Computing
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This paper is primarily focused on the description of the human centered interface specifications, research and implementations for systems geared towards the well-being of aged people. ...
Subspace learning methods are based on principles originally used for statistical pattern recognition and have been successfully implemented in many computer vision problems, such as, facial expression ...
Facial Expression Recognition based on subspace learning Facial expressions and gestures complement verbal communication in everyday life, conveying information about emotion, mood and ideas [15] . ...
doi:10.1007/978-3-642-23169-8_1
dblp:conf/icmmi/TefasP11
fatcat:psnls5sbd5bqhn3wawia7l74x4
Emotion Analysis Based on Facial Expression Recognition in Virtual Learning Environment
2017
International Journal of Computer and Communication Engineering
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Application of facial expression recognition is performed on Magic Learning which is a 3D Virtual Learning Environment (3DVLE) developed by our laboratory and experimental results suggest that our method ...
The video data and facial expression images are ...
Higher-Order Singular Value Decomposition (HOSVD) [4] is a general n-factor analysis method. HOSVD has been applied to human face recognition and facial expression recognition. ...
doi:10.17706/ijcce.2017.6.1.49-56
fatcat:dw2n4wynebduflpwynbk5ck5ze
Utility Preserved Facial Image De‐identification Using Appearance Subspace Decomposition
2021
Chinese journal of electronics
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Automated human facial image deidentification is a much-needed technology for privacypreserving social media and intelligent surveillance applications. ...
models the level of discriminativeness on identity and utility. ...
Utility Preserved Facial Image De-Identification Using Appearance Subspace Decomposition Our novel appearance space analysis method is based on the hypothesis that the appearance of a human face is influenced ...
doi:10.1049/cje.2021.03.004
fatcat:2gprptvnwjdypceidmcz4hoyxi
Eliminating other-race effect for multi-ethnic facial expression recognition
2019
Mathematical Foundations of Computing
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Hence, ethnic-sensitive features are then determined by an entropy-based feature selection method and discarded to depress their influence on facial expression recognition. ...
This work proposes an ICA-based method to eliminate the other-race effect in automatic 3D facial expression recognition. ...
The proposed method is evaluated on the BU-3DFE database [24] , which is originally collected for 3D facial expression recognition. ...
doi:10.3934/mfc.2019004
fatcat:5jjfd6fjujdg7a4c3g7zx3tkhm
Dual-threshold Based Local Patch Construction Method for Manifold Approximation And Its Application to Facial Expression Analysis
2019
2019 27th European Signal Processing Conference (EUSIPCO)
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In this paper, we propose a manifold based facial expression recognition framework which utilizes the intrinsic structure of the data distribution to accurately classify the expression categories. ...
We propose the dual-threshold based local patch (DTLP) extraction method for constructing the local subspaces, which in turn approximates the expression manifold. ...
INTRODUCTION Facial expression is the primary cue to recognize and interpret human emotion. ...
doi:10.23919/eusipco.2019.8902603
dblp:conf/eusipco/HappyDR19
fatcat:wty7ylz6mfab7lci4zxxnip77y
Audio-visual emotion recognition in adult attachment interview
2006
Proceedings of the 8th international conference on Multimodal interfaces - ICMI '06
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Based on the assumption that facial expression and vocal expression be at the same coarse affective states, positive and negative emotion sequences are labeled according to Facial Action Coding System ...
In this paper, we explore audio-visual emotion recognition in a realistic human conversation setting--Adult Attachment Interview (AAI). ...
The corresponding facial expression subspaces are called optimal facial expression subspaces for each method. ...
doi:10.1145/1180995.1181028
dblp:conf/icmi/ZengHFHRW06
fatcat:xxeae5xbk5f43ndlxahd3cnfa4
Improving subspace learning for facial expression recognition using person dependent and geometrically enriched training sets
2011
Neural Networks
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Moreover, person dependent training is proven to be much more accurate for facial expression recognition than generic learning. ...
In this paper, the robustness of appearance-based subspace learning techniques in geometrical transformations of the images is explored. ...
Conclusions Facial expressions consist an integral part of human nonverbal communication. Subspace learning methods have become a frequently used tool to perform facial expression recognition. ...
doi:10.1016/j.neunet.2011.05.015
pmid:21820862
fatcat:77jqe7m6izgazdpgeugphnhe3q
An unsupervised learning approach for facial expression recognition using semi-definite programming and generalized principal component analysis
2010
Image Processing: Algorithms and Systems VIII
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In this paper, we consider facial expression recognition using an unsupervised learning framework. ...
We show that different facial expressions reside on distinct subspaces if the manifold is unfolded. ...
In this paper, we propose an unsupervised learning approach to facial expression recognition, where we show that different facial expressions reside on distinct subspaces if the manifold of facial images ...
doi:10.1117/12.839982
dblp:conf/ipas/GholamiHT10
fatcat:qso3eewfrfafhlx2xix25rbwbe
Facial Expression Recognition Based on Complexity Perception Classification Algorithm
[article]
2018
arXiv
pre-print
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in most facial expression recognition systems. ...
Facial expression recognition (FER) has always been a challenging issue in computer vision. ...
As we all know facial expression is a major way of expressing human emotions. ...
arXiv:1803.00185v1
fatcat:lymwudzakbgudb3z3cmmwrtofa
Improving the Robustness of Subspace Learning Techniques for Facial Expression Recognition
[chapter]
2010
Lecture Notes in Computer Science
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In this paper, the robustness of appearance-based, subspace learning techniques for facial expression recognition in geometrical transformations is explored. ...
Based on systematic experiments, the database enrichment with translated, scaled and rotated images is proposed for confronting the low robustness of subspace techniques for facial expression recognition ...
Subspace learning techniques followed by well known classifiers are among the most used methods for human facial expression recognition. ...
doi:10.1007/978-3-642-15819-3_63
fatcat:prajc5pr7zcefbcbwxlvbqrnua
Emotion recognition from scrambled facial images via many graph embedding
2017
Pattern Recognition
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The benchmark results demonstrated that the proposed method can apparently improve the recognition accuracy, making our method a promising candidate for the scrambled facial expression recognition in the ...
In our experiments, the proposed MGE was tested on three scrambled facial expression datasets: JAFFE, MUG and CK++. ...
Later, nonlinear manifold learning [31~34] have brought out a number of new methods for face recognition, such as Laplacianface [33] and Tensor subspace [34] . ...
doi:10.1016/j.patcog.2017.02.003
fatcat:bmwh4qo4zbd7hapgidktaa4xxu
Deep features-based expression-invariant tied factor analysis for emotion recognition
2017
2017 IEEE International Joint Conference on Biometrics (IJCB)
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Furthermore, we compared the performance of our deep learning-based temporal model with recent dynamic facial expression recognition methods for each expression. ...
The overall facial expression recognition rate is 97.23% for deep learning-based video data. ...
doi:10.1109/btas.2017.8272741
dblp:conf/icb/MunasingheFS17
fatcat:zur4jl6qcfai5aq5p3zgfz2p4i
Cross-database non-frontal facial expression recognition based on transductive deep transfer learning
[article]
2018
arXiv
pre-print
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The final experimental results show that our transductive deep transfer network outperforms the state-of-the-art cross-database facial expression recognition methods. ...
In this paper, we proposed a novel transductive deep transfer learning architecture based on widely used VGGface16-Net for this problem. ...
This phenomenon shows that transductive transfer learning method based on group sparse learning method can also achieve good results in complex cross-database non-frontal facial expression recognition ...
arXiv:1811.12774v1
fatcat:pwkj2zbx7rg4pjlfaoo4uut33m
Facial expression decomposition
2003
Proceedings Ninth IEEE International Conference on Computer Vision
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We propose a simultaneous face and facial expression recognition algorithm, which can classify the given image into one of the seven basic facial expression categories, and then other facial expressions ...
We learn the expression subspace and person subspace from a corpus of images showing seven basic facial expressions, rather than resort to expert-coded facial expression parameters as in [3] . ...
Facial expression recognition is based on the cosine distance between test expression vector from Equation 6
Figure 2 . 2 Facial
Figure 3 . 3 *. ...
doi:10.1109/iccv.2003.1238452
dblp:conf/iccv/WangA03
fatcat:bre6dckgyrbdxgzvdnii5h34ba
A solution for facial expression representation and recognition
2002
Signal processing. Image communication
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We focus on the problem of facial expression recognition to demonstrate this technique. ...
This method provides a low-dimensional representation subspace which has been optimized to improve the classification accuracy. ...
For each of these facial parts, we independently construct their representation and recognition subspace by applying Sorted PCA plus LDA method on a learning set containing N ¼ 300 samples. ...
doi:10.1016/s0923-5965(02)00076-0
fatcat:6gayc4deevayrmrjbeariu6yqm
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