Face Emotion Detection Using OpenCV

Abstract Face Emotion Detection is a technology that leverages Artificial Intelligence (AI) and Computer Vision to analyze and classify human emotions based on facial expressions. This system utilizes image processing, feature extraction, and machine learning techniques to identify emotional states such as happiness, sadness, anger, surprise, fear, disgust, and neutrality By processing facial landmarks and dynamic changes in expressions, the technology enables accurate emotion recognition. he application of face emotion detection spans various fields, including healthcare, where it aids in early diagnosis of mental health conditions; education, for monitoring student engagement; retail, to gauge customer satisfaction; and security, for identifying unusual or suspicious behaviour. Key Words: Face Emotion Detection human emotion, machine learning, healthcare

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Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-03-27
DOI
https://doi.org/10.55041/ijsrem43024
Primary Topic
IoT-based Smart Home Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Face Emotion Detection Using OpenCV

K. Vikram, Prasath V. B. Surya, P Kanish, Mrs. A. Mohanadevi
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
IoT-based Smart Home Systems
article

Face Emotion Detection Using OpenCV

K. Vikram, Prasath V. B. Surya, P Kanish, Mrs. A. Mohanadevi
article en

Abstract

Abstract Face Emotion Detection is a technology that leverages Artificial Intelligence (AI) and Computer Vision to analyze and classify human emotions based on facial expressions. This system utilizes image processing, feature extraction, and machine learning techniques to identify emotional states such as happiness, sadness, anger, surprise, fear, disgust, and neutrality By processing facial landmarks and dynamic changes in expressions, the technology enables accurate emotion recognition. he application of face emotion detection spans various fields, including healthcare, where it aids in early diagnosis of mental health conditions; education, for monitoring student engagement; retail, to gauge customer satisfaction; and security, for identifying unusual or suspicious behaviour. Key Words: Face Emotion Detection human emotion, machine learning, healthcare

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(03)
Openalex Percentile: Top 95%
IoT-based Smart Home Systems
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