Proceedings ArticleDOI
Study of video based facial expression and emotions recognition methods
Husam Salih,Lalit Kulkarni +1 more
- pp 692-696
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TLDR
The methodologies in terms of feature extraction and classification used in facial expression and/or emotion recognition methods with their comparative study are presented, which is done based on accuracy, implementation tool, advantages and disadvantages.Abstract:
In real life scenario, facial expressions and emotions are nothing but responses to the external and internal events of human being. In human computer interaction, recognition of end user's expressions and emotions from the video streaming plays very important role. In such systems it is required to track the dynamic changes in human face movements quickly in order to deliver the required response system. The one real time application is physical fatigue detection based on facial detection and expressions such as driver fatigue detection in order to prevent the accidents on road. Face expression based physical fatigue analysis or detection is out of scope of this paper, but this paper reveal study on different methods those are presented recently for facial expression and/or emotions recognition using video. This paper presenting the methodologies in terms of feature extraction and classification used in facial expression and/or emotion recognition methods with their comparative study. The comparative study is done based on accuracy, implementation tool, advantages and disadvantages. The outcome of this paper is the current research gap and research challenges those are still open to solve for video based facial detection and recognition systems. The survey on recent methods is appropriately presented throughout this paper by considering future research works.read more
Citations
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Journal ArticleDOI
A Review on Automatic Facial Expression Recognition Systems Assisted by Multimodal Sensor Data
TL;DR: This survey comprehensively discusses three significant challenges in the unconstrained real-world environments, such as illumination variation, head pose, and subject-dependence, which may not be resolved by only analysing images/videos in the FER system and introduces three categories of sensors that may help improve the accuracy and reliability of an expression recognition system.
Journal ArticleDOI
Learning Hierarchical Emotion Context for Continuous Dimensional Emotion Recognition From Video Sequences
TL;DR: A novel three-stage method is proposed to learn hierarchical emotion context information (feature- and label-level contexts) for predicting affective dimension values from video sequences to highlight that incorporating both feature/label level dependencies and context information is a promising research direction for predicting the continuous dimensional emotion.
Journal ArticleDOI
A Two-Stage Spatiotemporal Attention Convolution Network for Continuous Dimensional Emotion Recognition From Facial Video
TL;DR: In this paper, a two-stage spatiotemporal attention temporal convolutional network (TS-SATCN) is proposed for continuous dimensional emotion recognition of facial videos, where the first stage generates an initial recognition result that is later fed into the second stage for correction.
Proceedings ArticleDOI
Fatigue Detection System for the Drivers Using Video Analysis of Facial Expressions
TL;DR: A framework is developed to detect the fatigue-ness from tracking the cornea of eyes by focusing on the face of the driver by utilizing image morphological changes like dilution, erosion, image segmentation like background elimination and Circular Hough Transform to detectCornea of an eye on the captured images on drivers.
Book ChapterDOI
Integration of Driver Behavior into Emotion Recognition Systems: A Preliminary Study on Steering Wheel and Vehicle Acceleration
TL;DR: This work proposes a multimodal system which is based on facial expressions and driver specific behavior including steering wheel usage and the change in vehicle acceleration to build a structure which continuously classifies the emotions in an efficient and non-intrusive manner.
References
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Journal ArticleDOI
Robust Representation and Recognition of Facial Emotions Using Extreme Sparse Learning
TL;DR: This paper proposes an approach called extreme sparse learning, which has the ability to jointly learn a dictionary (set of basis) and a nonlinear classification model and presents a new local spatio-temporal descriptor that is distinctive and pose-invariant.
Journal ArticleDOI
Spatiotemporal feature extraction for facial expression recognition
TL;DR: This study proposes a novel approach for appearance-based facial feature extraction to perform the task of facial expression recognition on video sequences and shows superior performance compared with the state-of-the-art approaches.
Proceedings ArticleDOI
Face recognition and facial expression identification using PCA
TL;DR: It is concluded that PCA is a good technique for face recognition as it is able to identify faces fairly well with varying illuminations, facial expressions etc.
Posted Content
A Facial Expression Classification System Integrating Canny, Principal Component Analysis and Artificial Neural Network
TL;DR: In this article, a novel approach using Canny, Principal Component Analysis (PCA) and Artificial Neural Network (ANN) was proposed for facial expression classification using the JAFFE database.
Journal ArticleDOI
Facial video-based detection of physical fatigue for maximal muscle activity
TL;DR: Experimental results show that the proposed system outperforms video-based existing system for physical fatigue detection and reduces erroneous results by discarding low quality faces that occurred in a video sequence due to problems in realistic lighting, head motion, and pose variation.
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