Human Emotion Detection Through Facial Expressions

ABSTRACT

Human communicates to show their emotion through different modalities like speech, body language and facial. However, facial expression is distinct because speech and body depends on language and culture respectively.

This project states the techniques of detecting human emotion through facial expressions. Facial expression has found a lot of applications in law enforcement, human computer interaction, detection sleeping driver, military, robotics, psychology etc.

The proposed application automatically captured frontal face from a still image or video, then histogram of oriented gradient (HOG) is deployed to extract facial features from the facial expressions. Support vector machine (SVM) is used for classification into seven basic emotions, which includes anger, disgust, fear, happy, neutral, sad, and surprise. In this project, a Matlab software is used to achieve the real time human emotion. Human communicates to show their emotion through different modalities like speech, body language and facial. However, facial expression is distinct because speech and body depends on language and culture respectively.

This project states the techniques of detecting human emotion through facial expressions. Facial expression has found a lot of applications in law enforcement, human computer interaction, detection sleeping driver, military, robotics, psychology etc.

The proposed application automatically captured frontal face from a still image or video, then histogram of oriented gradient (HOG) is deployed to extract facial features from the facial expressions. Support vector machine (SVM) is used for classification into seven basic emotions, which includes anger, disgust, fear, happy, neutral, sad, and surprise. In this project, a Matlab software is used to achieve the real time human emotion.

Human communicates to show their emotion through different modalities like speech, body language and facial. However, facial expression is distinct because speech and body depends on language and culture respectively.

This project states the techniques of detecting human emotion through facial expressions. Facial expression has found a lot of applications in law enforcement, human computer interaction, detection sleeping driver, military, robotics, psychology etc.

The proposed application automatically captured frontal face from a still image or video, then histogram of oriented gradient (HOG) is deployed to extract facial features from the facial expressions. Support vector machine (SVM) is used for classification into seven basic emotions, which includes anger, disgust, fear, happy, neutral, sad, and surprise. In this project, a Matlab software is used to achieve the real time human emotion.

Human communicates to show their emotion through different modalities like speech, body language and facial. However, facial expression is distinct because speech and body depends on language and culture respectively.

This project states the techniques of detecting human emotion through facial expressions. Facial expression has found a lot of applications in law enforcement, human computer interaction, detection sleeping driver, military, robotics, psychology etc.

The proposed application automatically captured frontal face from a still image or video, then histogram of oriented gradient (HOG) is deployed to extract facial features from the facial expressions. Support vector machine (SVM) is used for classification into seven basic emotions, which includes anger, disgust, fear, happy, neutral, sad, and surprise. In this project, a Matlab software is used to achieve the real time human emotion.