Facial Expression Emotion Recognition

With an emphasis on improving accessibility for those with visual impairments by utilizing real-time aural feedback, this study presents a novel method for identifying emotions and facial expressions. Effective communication relies heavily on facial expressions, but people who are blind or visually impaired sometimes find it difficult to interpret the emotional messages that are expressed through nonverbal facial cues. This project attempts to create an inclusive system that helps visually impaired individuals identify and understand emotions in their social surroundings by utilizing state-of-the-art computer vision algorithms in combination with aural feedback. The suggested method accurately detects and classifies a range of facial emotions from live video streams using a deep learning-based architecture. When an emotion is identified, the system uses synthesized audio cues to tell the user

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Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-02-20
DOI
https://doi.org/10.22214/ijraset.2025.66971
Primary Topic
Face and Expression Recognition
Type
article
Field-Weighted Citation Impact
0.00
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article

Facial Expression Emotion Recognition

Manav Kathuria
International Journal for Research in Applied Science and Engineering Technology
Face and Expression Recognition
article

Facial Expression Emotion Recognition

Manav Kathuria
article en

Abstract

With an emphasis on improving accessibility for those with visual impairments by utilizing real-time aural feedback, this study presents a novel method for identifying emotions and facial expressions. Effective communication relies heavily on facial expressions, but people who are blind or visually impaired sometimes find it difficult to interpret the emotional messages that are expressed through nonverbal facial cues. This project attempts to create an inclusive system that helps visually impaired individuals identify and understand emotions in their social surroundings by utilizing state-of-the-art computer vision algorithms in combination with aural feedback. The suggested method accurately detects and classifies a range of facial emotions from live video streams using a deep learning-based architecture. When an emotion is identified, the system uses synthesized audio cues to tell the user

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(2)
Chaudhary Charan Singh University (IN)
Openalex Percentile: Top 98%
Face and Expression Recognition
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