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Impact of Deep Learning Approaches on Facial Expression Recognition in Healthcare Industries
IEEE Transactions on Industrial Informatics, 2022A facial expression recognition system that can provide quick assistance to the healthcare system and exceptional services to the patients is proposed in this article. The implementation of this work is divided into three components.
Carmen Bisogni +4 more
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Former-DFER: Dynamic Facial Expression Recognition Transformer
ACM Multimedia, 2021This paper proposes a dynamic facial expression recognition transformer (Former-DFER) for the in-the-wild scenario. Specifically, the proposed Former-DFER mainly consists of a convolutional spatial transformer (CS-Former) and a temporal transformer (T ...
Zengqun Zhao, Qingshan Liu
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Relation-Aware Facial Expression Recognition
IEEE Transactions on Cognitive and Developmental Systems, 2022Research on facial expression recognition has been moving from the constrained lab scenarios to the in-the-wild situations and has made progress in recent years.
Yifan Xia +4 more
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IEEE Transactions on Industrial Informatics
How to automatically recognize facial expression has caused concerns in industrial human–robot interaction. However, facial expression recognition (FER) is susceptible to problems, such as occlusion, arbitrary orientations, and illumination.
Hai Liu +6 more
semanticscholar +1 more source
How to automatically recognize facial expression has caused concerns in industrial human–robot interaction. However, facial expression recognition (FER) is susceptible to problems, such as occlusion, arbitrary orientations, and illumination.
Hai Liu +6 more
semanticscholar +1 more source
Simultaneous Facial Feature Tracking and Facial Expression Recognition
IEEE Transactions on Image Processing, 2013The tracking and recognition of facial activities from images or videos have attracted great attention in computer vision field. Facial activities are characterized by three levels. First, in the bottom level, facial feature points around each facial component, i.e., eyebrow, mouth, etc., capture the detailed face shape information.
Yongqiang, Li +3 more
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Fine-Grained Facial Expression Recognition in the Wild
IEEE Transactions on Information Forensics and Security, 2021Over the past decades, researches on facial expression recognition have been restricted within six basic expressions (anger, fear, disgust, happiness, sadness and surprise).
Liqian Liang +4 more
semanticscholar +1 more source
2003
The most expressive way humans display emotions is through facial expressions. Humans detect and interpret faces and facial expressions in a scene with little or no effort. Still, development of an automated system that accomplishes this task is rather difficult. There are several related problems: detection of an image segment as a face, extraction of
Nicu Sebe, Michael S. Lew
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The most expressive way humans display emotions is through facial expressions. Humans detect and interpret faces and facial expressions in a scene with little or no effort. Still, development of an automated system that accomplishes this task is rather difficult. There are several related problems: detection of an image segment as a face, extraction of
Nicu Sebe, Michael S. Lew
openaire +1 more source
4D facial expression recognition
2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), 2011In this paper, we focus on discrete expression classification using dynamic 3D sequences (4D data) recording the facial movements. A robust approach for registering 4D data is proposed and a variant of local binary patterns on three orthogonal planes is used for feature extraction.
Tianhong Fang +3 more
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Dynamic Facial Expression Recognition Using Longitudinal Facial Expression Atlases
2012In this paper, we propose a new scheme to formulate the dynamic facial expression recognition problem as a longitudinal atlases construction and deformable groupwise image registration problem. The main contributions of this method include: 1) We model human facial feature changes during the facial expression process by a diffeomorphic image ...
Zhao Guoying +2 more
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Facial Expression Recognition Using Facial Graph
2015Automatic analysis of human facial expression is one of the challenging problems in machine vision systems. It has many applications in human-computer interactions, social robots, deceit detection, interactive video and behavior monitoring. In this paper, we developed a new method for automatic facial expression recognition based on verifying movable ...
Sina Mohseni +3 more
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