Author(s) :

Lokesh patil Lokesh patil, Jagrati patil, Anushree khambayte, Vinit patil.

Volume/Issue :

Abstract :

This paper presents the idea related to automated live facial emotion recognition through image processing and artificial intelligence (AI) techniques. It is a challenging task for a computer vision to recognize as same as humans through AI. Face detection plays a vital role in emotion recognition. Emotions are classified as happy, sad, disgust, angry, neutral, fear, and surprise. Other aspects such as speech, eye contact, frequency of the voice, and heartbeat are considered. Nowadays face recognition is more efficient and used for many real-time applications due to security purposes. We detect emotion by scanning (static) images or with the (dynamic) recording. Features extracting can be done like eyes, nose, and mouth for face detection. The convolutional neural network (CNN) algorithm follows steps as max-pooling (maximum feature extraction) and flattening.and the use the gabor transform to extract the emotion features of the area.

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