Facial Emotion Recognition Using Osmotic Computing

View Sample PDF

Author(s): P. Aurchana (Malla Reddy University, India), R. Indhumathi (Idhaya College for Women, India), G. Revathy (SASTRA University, India)and A. Ramalingam (Sri Manakula Vinayagar Engineering College (Autonomous), India)
Copyright: 2024
Pages: 14
Source title: Advanced Applications in Osmotic Computing
Source Author(s)/Editor(s): G. Revathy (SASTRA University, India)
DOI: 10.4018/979-8-3693-1694-8.ch001

Keywords: Cloud Computing / Computer Science & IT / Engineering Science Reference / Systems and Software Engineering

Purchase

View Facial Emotion Recognition Using Osmotic Computing on the publisher's website for pricing and purchasing information.

Abstract

Emotion recognition refers to the process of identifying the emotions expressed by an individual, typically through their facial expressions, speech, body language, and sometimes physiological signals like heart rate or skin conductance. In this chapter, facial expression is used to recognise. Emotions like happiness, sadness, anger, fear, surprise, and disgust are typically recognized. This chapter aims at developing a real-time approach to classification of facial emotions such as happy, normal, yawn, and sleep in a real-time context. For this, images are captured using sensors and stored in a cloud storage bucket in which the processing is done. The facial emotions are identified through the use of Haar cascade classifiers. The histogram-oriented gradients features are extracted in the detected facial emotion images, and the extracted features are classified by using machine learning models support vector machine and k-nearest neighbour classifiers as happy, normal, yawn, and sleep. The suggested system outperforms other current systems when tested with real-time datasets.

The IRMA Community

Research IRM

Facial Emotion Recognition Using Osmotic Computing

Purchase

Abstract

Related Content

IRMA Sponsors