International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 09 Issue: 06 | June 2022
p-ISSN: 2395-0072
www.irjet.net
FACIAL EMOTION RECOGNITION Kavya K1, Misha Bharathi S2, Namratha B R3, Nandini V 4 Dr. Renuka Devi M N, Dept. of Computer Science, Dayananda Sagar University, Karnataka, India ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - Human emotions are mental states of sentiments that occur without conscious effort and are accompanied by physiological changes in facial muscles that result in facial expressions. As a result, this study provides an approach for real-time recognizing facial emotion using image processing and AI techniques. Emotion recognition relies heavily on face detection. Sad, glad, surprise, fear, anger, neutral, and other emotions are all characterized as such. The Haar cascade method and the Convolutional Neural Network are used here. In the CNN technique, processes such as pooling and followed by flattening, whereas the Haar cascade algorithm uses Haar feature selection and cascading classifiers. Face emotion recognition is more effective nowadays, and many applications use it in real time for security purposes.
Eyebrows drawn up, upper eyelids drawn up, and lips extended are all signs of fear.
2. LITERATURE SURVEY
Key Words: Facial emotion recognition,CNN,Haar Cascade
1.INTRODUCTION Facial Emotion Detection is a technique that analyses facial expressions in photos and videos to disclose information about a person's emotional state. People use facial expressions and verbal tones to infer other people's emotional states, such as joy, sadness, and rage. We're using a trained dataset which includes constant dynamic graphics, photographs collected from videos or in real time. Those dataset picture classifiers appear to be basic, yet they are extremely sensitive to each individual's facial emotions. Since the dawn of the smartphone era, the security of unlocking a phone has been steadily improving. As technology advances, we choose colour image face expression recognition as our project to detect a person's emotion, such as happiness, rage, melancholy, and so on. Emotions have a vital influence not only in our interpersonal relationships, but also in how we utilise computers. Some traits, such as elevated lip corners and cheeks, creases, and muscular tightening around the eyes, can be used to identify a happy emotion. Similarly, angry features can be expressed by pulling up the upper lids, tightening the lips, and pulling up the lower lids. Eyebrows pulled down, upper lip pulled up, and nose furrowed are all disgusting traits. Eyelids pushed up, mouth hangs open, and full eyebrow pulled up are all unexpected traits. All features are placed in their proper placements as neutral features.
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