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primary topic: Emotion Detection Using Facial Expression Involving Occlusions and Tilt

Emotion Detection Using Facial Expression Involving Occlusions and Tilt
type: AcademicArticle
type: Article
abstract: Facial emotion recognition (FER) is an important and developing topic of research in the field of pattern recognition. The effective application of facial emotion analysis is gaining popularity in surveillance footage, expression analysis, activity recognition, home automation, computer games, stress treatment, patient observation, depression, psychoanalysis, and robotics. Robot interfaces, emotion-aware smart agent systems, and efficient human–computer interaction all benefit greatly from facial expression recognition. This has garnered attention as a key prospect in recent years. However, due to shortcomings in the presence of occlusions, fluctuations in lighting, and changes in physical appearance, research on emotion recognition has to be improved. This paper proposes a new architecture design of a convolutional neural network (CNN) for the FER system and contains five convolution layers, one fully connected layer with rectified linear unit activation function, and a SoftMax layer. Additionally, the feature map enhancement is applied to accomplish a higher detection rate and higher precision. Lastly, an application is developed that mitigates the effects of the aforementioned problems and can identify the basic expressions of human emotions, such as joy, grief, surprise, fear, contempt, anger, etc. Results indicate that the proposed CNN achieves 92.66% accuracy with mixed datasets, while the accuracy for the cross dataset is 94.94%.
date: 2022-11
volume: 12
issue: 22
is part of: Applied Sciences
status: peerReviewed
status: published
author list: authors
type: EPrint
type: ArticleEPrint
is part of: repository
has document: Emotion Detection Using Facial Expression Involving Occlusions and Tilt (Texto)
has document: Emotion Detection Using Facial Expression Involving Occlusions and Tilt (Otro)
subject: Engineering

Emotion Detection Using Facial Expression Involving Occlusions and Tilt (Texto)
type: Document
has file: applsci-12-11797-v2.pdf
has part: applsci-12-11797-v2.pdf

Applied Sciences
type: Collection
issn: 20763417

Carmen Lilí Rodríguez Velasco
type: Person
given name: Carmen Lilí
family name: Rodríguez Velasco

Furqan Rustam
type: Person
given name: Furqan
family name: Rustam

Awais Salman Qazi
type: Person
given name: Awais Salman
family name: Qazi

Mónica Gracia Villar
type: Person
given name: Mónica
family name: Gracia Villar

Muhammad Shoaib Farooq
type: Person
given name: Muhammad Shoaib
family name: Farooq

Imran Ashraf
type: Person
given name: Imran
family name: Ashraf

Emotion Detection Using Facial Expression Involving Occlusions and Tilt (Otro)
type: Document
is version of: Emotion Detection Using Facial Expression Involving Occlusions and Tilt (Texto)
is volatile version of: Emotion Detection Using Facial Expression Involving Occlusions and Tilt (Texto)
is index codes version of: Emotion Detection Using Facial Expression Involving Occlusions and Tilt (Texto)
has file: indexcodes.txt
has part: indexcodes.txt

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primary topic: Emotion Detection Using Facial Expression Involving Occlusions and Tilt

Engineering
type: Concept
preferred label: Ingeniería @es